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U.S. Department of Labor
In this issue
Employment in d ay care
Health insurance am ong families
Fatalities of the self-em ployed
Unemployment indicators
Incom e inequality
Textile and apparel em ploym ent
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M l Table of Contents
■
i
j Federal Reserve Bank
M st. Quis N
T
H
L
Y
L
A
B
O
REVIEW
A ugust 1995
R
Volum e 118, N um ber 8
Family matters
Editor-in-Chief
Deborah P. Klein
Boom in day care industry the result of many social changes
Executive Editor
Richard M. Devens, Jr.
Five major factors are responsible
for the rapid employment increase in this industry
William Goodman
Managing Editor
Health insurance coverage for families with children
Anna Huffman Hill
Regardless of incomes, families without coverage are less likely
to receive care than are partially insured families
Geoffrey D. Paulin and Elizabeth Dietz
Editors
Brian I. Baker
Leslie Brown Joyner
Mary K. Rieg
Stephen Singer
Editorial Assistant
Ernestine Patterson Leary
Production Manager
3
13
Other articles
Self employed individuals fatally injured at work
24
Individuals who work for themselves typically face higher risk
of fatalities, compared with their wage and salary counterparts
Martin E. Personick and Janice A. Windau
Dennis L. Rucker
International unemployment indicators, 1983-93
Production Assistants
Catherine D. Bowman
Phyllis L. Lott
Edith W. Peters
Catherine A. Stewart
Contributors
Michael H. Cimini
Constance B. DiCesare
Charles A. Muhl
Polly A. Phipps
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Federal Reserve Bank of St. Louis
31
Sweden has the largest increase in labor underutilization
when part-time work for economic reasons is taken into account
Constance Sorrentino
A surge in growing income inequality?
51
A reported surge in income inequality indicates that patterns
of employment growth were consistent with greater income dispersion
Paul Ryscavage
Unraveling employment trends in textiles and apparel
62
These two closely related industries differ in the reasons
for their job losses and the prognosis for their future
Lauren A. Murray
Departments
Labor month in review
Industrial relations
Book reviews
Current labor statistics
2
73
77
79
Labor Month in Review
The August Review
Chamovitz reviews Trade and Labor Stan
dards: A Review of the Issues (edited by Gary
Job, health, and family are cardinal sources
o f well-being for working Americans. The
broad demographic, social, and economic
changes shaping the family’s involvement
in economic life have been covered exten
sively in the press, academic journals, and
this Review. This month, we examine some
more subtle effects of the forces affecting
today’s working family.
As William Goodman notes in our lead
article, “The daily life of schoolchildren has
changed dramatically in the last 20 years.”
They are much less likely to be directly su
pervised by relatives and much more likely
to be watched by the employees of the rap
idly growing day care industry. Goodman
proceeds to weave together the five major
factors that have led to a tripling of employ
ment in the private day care industry since
estimates of its employment were first pub
lished by the Bureau in 1972: the growing
number o f children, a rising percentage of
mothers participating in the labor force,
more public spending on child care, tax poli
cies providing additional benefits to fami
lies, and more widespread corporate and
private initiatives to provide day care.
In the June Review, we reported on the
incidence of and access to health insurance
as an employment benefit. In this issue,
Geoffrey D. Paulin and Elizabeth M. Dietz
rigorously explore the intricate interactions
o f employment, income, and health insur
ance coverage on health care spending in
families with children. Perhaps the most
interesting o f these analyses shows that
the expenditure on drugs and other medi
cal supplies is an important measure of
those who “when they become ill ... be
com e well faster.” In their econometric
analysis, persons in fully and partially in
sured families are much more likely to in
cur such expenditures, even when all else
is held constant.
Other articles include Martin E. Personick and Janice A. Windau on fatal inju
ries among the self-employed, an interna
tional comparison of alternative measures
of the underutilization of labor written by
Constance Sorrentino, an evaluation of in
come inequality and the possible impact of
new survey methods on its measurement by
1994 Klein award winner Paul Ryscavage,
and Lauren A. Murray’s analysis of trends
in textile and apparel jobs. M ichael H.
Cimini and Charles J. Muhl present their
regular analysis of current developments in
industrial relations. Pat Nielsen reviews Why
Our Kids D on’t Study: An Economist’s
Perspective (by John D. Owen) and Steven
2
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August 1995
Fields).
The new retirem ent
The incidence of retirement benefits was
fairly stable in the 5-year period from 1989
to 1994, but the form o f benefit shifted sig
nificantly, according to the Pension and
Welfare Benefits Administration of the U.S.
Department o f Labor. In their report, Re
tirement Benefits of American Workers: New
Findings from the September 1994 Current
Population Survey, analysts Dan Beller and
Richard Hinz find, “Virtually all retirees
receive Social Security benefits after the age
of 65 and somewhat less than one-half are
able to supplement this income with a pri
vate pension benefit.”
The most significant change has been in
the form in which retirement benefits are
received. About 48 percent o f pension re
cipients in 1994 received an annuity as part
o f their income package, compared with
fully 60 percent of recipients in 1989. In
1994, just over half of pension beneficia
ries received only a lump-sum distribution.
Overall, Social Security and private ben
efits are replacing about 60 percent of nomi
nal earnings. But, only a small proportion
o f annuitants receive cost-of-living adjust
ments. As a result, current retirees have a
“real replacement rate” of less than one-half
the purchasing power of their prior earn
ings. “This,” the report concludes, “will re
quire them to rely on individual savings or
continue to keep working during retirement
if they wish to maintain their standard of
living.”
Em ployee density
Four of New York City’s five boroughs are
among the 10 counties in the United States
with the greatest “employment density”
(that is, the number o f persons employed in
the county per square mile of county area).
Kent Halstead reports in Wages and Cost
of Living: 508 County Indexes that Man
hattan (New York) is the most dense, with
75,588 employees per square mile, followed
by San Francisco (California) with a den
sity of 9,760 employees. The other “dense”
counties are Boston (Massachusetts), 7,457;
Washington (District of Columbia), 5,893;
Brooklyn (New York), 5,167; Bronx (New
York), 4,053; Philadelphia (Pennsylvania),
3,999; Baltimore (Maryland), 3,998; Jersey
City (New Jersey), 3,885; and Queens (New
York), 3,667.
C yc lic a l loss
vs. regional growth
Differences in net job growth across States
are caused by variations in their rate of job
creation, while fluctuations in employment
over the business cycle are associated with
variations in the rate of job destruction. This
is the central finding o f Cyclical Versus
Secular Movements in Employment Cre
ation and Destruction ( n b e r Working Pa
per No. 5162) by Randall W. Eberts and Ed
ward Montgomery.
Because the State-to-State pattern of net
job dynamics is so different from the struc
ture o f cy clica l em ploym ent variation,
Eberts and Montgomery warn that policy
makers should be cautious in applying cy
clical models to regional issues. Specifi
cally, they suggest that “promoting new firm
creation and expansion might be more fruit
ful in the long run” for local economies be
cause their em ployment differences are
driven by differences in rates of job cre
ation. But, they note, “Clearly, definitive
policy recommendations must await a more
structural analysis o f the determinants of
job creation and destruction.”
Fewer J ap an ese
businesses
According to the June 1995 Japan Labor
Bulletin, a recent survey o f Japanese busi
nesses found that both the number of estab
lishments and the count of employees work
ing for them dropped below the levels
reported in the previous survey (1991).
“This clearly indicates that the adverse ef
fects of the economic slowdown following
the bursting of the financial bubble are enor
mous. It was the first such drop since 1947
when the survey was originated.” In April
1994, there were about 6.55 million privatesector firms in operation, a drop o f 0.2 per
cent from the 1991 survey. The total num
ber of employees at these firms was 54,366
million in 1994, a decrease o f 1.2 percent
from the earlier survey.
Next month
Next month’s Review will feature articles
on earnings mobility, how the intermittent
labor force affects women’s earnings, em
ployment in the security brokers and deal
ers industry, trends in unemployment insur
ance benefits, and a discussion of the old
and new measures o f educational attain
ment in the Current Population Survey. □
Employment in Day Care
Boom in d ay care industry
the result of m any social changes
The number of employees in the
day care industry has increased
at a much faster rate than working mothers;
five major factors are responsible
William Goodman
he daily life of preschool children in the
United States has changed dramatically
in the last 20 years. Because mothers of
young children are far more likely to work than
at any other time in the past, mother and child
now spend much less time at home.1 Further
more, far more relatives—particularly women—
also are employed, and have less time to spend
with nephews, nieces, young cousins, and grand
children. For these and other reasons, young chil
dren are more likely to attend day care centers.
During the 2 decades, employment in private-sector day care centers increased by more than 250
percent, gaining nearly 400,000jobs and continu
ing to grow during two of the four recessions in
the period. No single factor influencing the day
care industry and examined here has increased
as has employment in the industry. Instead, a
combination of at least five major factors drives
demand for the services of child-care centers.
T
Trends in day care jobs
William G o o d m a n
is an econom ist in
th e O ffic e o f
Em ploym ent a n d
U nem ploym ent
Statistics, Bureau of
Labor Statistics.
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Federal Reserve Bank of St. Louis
Employment growth in the day care industry since
1972 has been much more rapid than the growth
of most industries: overall, the number of day care
jobs has grown by approximately 250 percent, or
375,000 jobs. Growth occurred almost through
out the 22-year period, except for the early 1980’s,
during which two back-to-back recessions oc
curred. From early 1979 to summer of 1982,
30,000 jobs were lost in day care. Renewed
growth from fall 1982 to mid-1985 expanded the
number of jobs to above the preceding peak, and
strong growth has since continued. Unlike most
industries, child day care continued to expand vig
orously during the recessions of 1973-75 and
1990-91. Explanations for these movements, in
cluding the seemingly inconsistent behavior in the
various recessions, are discussed below.
Causes of growth
One way to begin an analysis of employment
growth in day care is to distinguish between
growth attributable to greater enrollment and the
effects of changes in the ratio of enrolled children
to staff. Fewer children per staff member generally
improve the quality of care. Consistent, regularly
timed estimates of the ratio of children to staff are
not available. But one publication calculates that
the average ratio of children to caregivers and
teachers in full-time centers (7 hours a day or
more) increased considerably, from 6.8 to 8.5
children per worker, between 1976 and 1990.2
Because a staff member supervised more children
in 1990, the change in the ratio pushed down
employment. If the ratio had remained unchanged,
employment in 1990 would have been greater by
M o n th ly
Labor
R e v ie w
A u g u s t 1995
3
Em ploym ent in D ay Care
S cope of study
This article primarily relies on estimates of employment
in day care establishments from the Bureau of Labor Sta
tistics monthly survey of employers. These statistics are
from the Current Employment Statistics program of b l s .
The c e s program produces estimates of employees on all
nonfarm payrolls except in private households, based on a
monthly survey of about 390,000 work sites.
Data from the survey appear in the monthly b l s peri
odical Employment and Earnings, c e s data in this article
are seasonally adjusted unless otherwise indicated.
For purposes of the survey, this article uses the Federal
Office of Management and Budget’s Standard Industrial
Classification Manual’s definition of the child day care
industry, which includes private-sector “establishments
primarily engaged in the care of infants or children, or in
providing pre-kindergarten education, where medical care
or delinquency correction is not a major element.”
Including the education of the very young is appropriate,
because a definite line between care and education cannot
be drawn; many day care centers include education in their
programs, and in earliest childhood, play and learning
cannot be distinguished clearly.
This definition of the day care industry includes large
and small companies doing business for profit or for other
purposes, such as social good. Secular and religious non
profit organizations and for-profit companies are included.
However, a few significant exclusions apply. Govern
ment day care— for example, day care centers within pub
lic school systems, or those provided by government agen
cies for employees—is not included in the child day care
110,000 in full-time centers alone.
Because fewer staff members now handle the same num
ber of children, enrollment increases must account for the
employment of larger numbers of teachers and child care
workers in the industry. Consistent measures of total enroll
ment of children in day care, at regularly timed intervals,
also are not available.3 However, an abundance of indirect
evidence indicates tremendous growth in enrollment. In ad
dition, one source concludes that enrollment in full-time early
education and care increased from 900,000 children in the
mid-1970’s to 3.8 million in 1990.4
Why enrollment grew
Several factors caused the growth in enrollment. Although
an increase in the population of children is the most obvious
cause, growth in the proportion of children who are in day
4
M onthly Labor Review August 1995
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industry data presented in this article, unless a separate,
private organization performs the work of the center. In
addition, if day care is provided onsite directly by an em
ployer for its own employees’ children, without the use of
a contractor but as a company-owned operation, the day
care personnel are not included. When care of children is
offered by an individual at their own residence, without
the use of any employees, the provider is not counted, as
the survey measures only employment on payrolls rather
than self-employed workers. Nannies and, in fact, all do
mestic workers also are excluded from the survey.
Because of the various exclusions, the estimates being
studied do not represent all child care workers in the coun
try. Trends in Government day care, child care provided
by employers for their employees’ children, care by do
mestic workers in the child’s home, and care by entrepre
neurs working in their own homes may not be exactly the
same as the trends of private-sector day care centers. But
an abundance of anecdotal evidence suggests that day care
provided directly by employers for their own employees’
children is growing fast.
Employment in the day care industry as estimated from
the survey includes not only employees directly caring for
children but all employees of day care companies. Ac
cording to the b l s Occupational Employment Survey, 8
percent of the child care industry’s employees are manag
ers or administrators, 15 percent are clerical workers, 33
percent are teachers, and 25 percent are child care work
ers. The remaining 19 percent are widely scattered among
a variety of other occupations.
care programs has had much more influence. The increas
ing percentage of children in day care reflects large gains in
the number of their mothers who have jobs.
U.S. population of youngsters. In 1990, children 3 to 5
years old accounted for 52 percent of day care enrollment;
children under 6 accounted for 74 percent.5 (See table 1.)
While the growth in the populations of these age groups has
been gradual, at 1 to 3 percent annually, the aggregate growth
of children younger than 6 from 1972 to 1994 has been 3
million. (See table 2 and chart 1.) The number of 3-to-5year-olds increased by 1.6 million.6
If the ratio of day care center employees to all children
under 6 is held constant at the 1972 rate, the increase in the
population of youngsters under 6 implies relatively slight
growth in employment: 22,000 day care employees, or just 6
percent of actual growth. Clearly, changes in these popula
tions are only a minor factor in the expansion of the industry.
Evidently, additional factors strongly affect demand.
Changes in the family. Children of working mothers are en
rolled in centers as a primary arrangement for care nearly
twice as frequently as children of mothers without jobs. As
of 1990, if school is excluded as a child care arrangement, 17
percent of children younger than 13 with employed mothers
were enrolled in a center as their primary arrangement;
among children under 13 with mothers who did not hold
jobs, 9 percent were enrolled in centers as a primary arrange
ment.7 The number and proportion of women at work have
increased greatly in the last 20 years, rising from 41 percent
in 1972 to 54 percent in 1993.8 (See table 2 and chart 1.)
The proportion of working mothers of children under 6 rose
by an even greater percentage: from 33 percent in 1975 to 53
percent in 1993. Mothers of children under 3 also greatly
increased their participation in employment, from 28 per
cent in 1975 to 49 percent in 1993. (See table 1.)
In 1975, 16 percent of mothers with children under 6 did
not have a spouse in the household; in 1993, that proportion
increased to 26 percent.9 One might expect that the absence
of a working husband from the household would be a major
explanation of why more mothers of young children are at
work, but mothers with a husband in the household increased
their jobholding far more. Between mothers of young chil
dren who had husbands with them and those who did not,
the percentages at work were fairly close in the mid-1970’s;
but women with spouses present increased considerably in
percentage employed, while those without spouses present
increased only slightly in percent employed. Exact percent
ages, derived from Current Population Survey data, are shown
in the following tabulation:
1975
1993
children10 become unavailable as a greater percentage of the
population becomes employed. From 1972 to 1993, the over
all employment-to-population ratio increased from 57.0 per
cent to 61.6 percent. Although the employment-to-popula
tion ratio of men decreased by 5 percent, the ratio among
women increased by 13 percentage points to 54.1 percent.
At the start of the latest post-recession period, from early
1991 to the end of 1993, job growth among women was great
est among 45-to-54-year-olds. Seventy-two percent of women
in that age range were employed at the end of the period11—
implying that a great many grandmothers and older aunts
are not available as they once were to watch children during
the day.
While comprehensive, clear statistics are not available to
show a shift from care by relatives to care in centers among
all children, the Census Bureau has estimated use of various
child-care arrangements by families with working mothers
and children under 5 in various years. The results indicate
that from 1977 to 1991, use of child care centers increased by
10 percentage points, from 13 percent of such families to 23
percent. Care by relatives other than parents dropped the
most, from 31 percent to 24 percent.
In addition, 1991 results appear to have been influenced
by the recession and the continued post-recession decline in
employment. An abnormally large number of laid-off rela
tives may have been temporarily available to care for chil
dren in 1991. Results from 1990, when employment was not
so abnormally depressed, may better typify the 1990’s. In
deed, 1990 shows more care in centers and less care by rela
tives than in 1991. From 1977 to 1990, care in centers more
than doubled, increasing from 13 percent to 28 percent, as
opposed to 23 percent in 1991. The following tabulation
shows the primary child care arrangement in families with
children under age 5 and a working mother in selected years
(in percent):12
1977 1985 1990 1991
Mothers of children under age 6:
With spouse in household.....................
Without spouse in household.................
32
42
56
44
Mothers of children aged 3 to 5:
With spouse in household.....................
Without spouse in household................
37
49
60
55
Changes in needs and preferences that caused more of these
mothers to go to work affected the group with a husband in
the household far more than those without a husband. The
group with a spouse present also is much larger. Women
who live with their husbands, therefore, made the far heavier
contribution to the increased employment of mothers of young
children.
The number of working women in general also is impor
tant as a factor in the demand for child care: not only moth
ers but also other relatives who might be available to watch
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Child cared for by—
Father.............................................
Relative other than parent.......
Nonrelative in child’s h o m e ....
Nonrelative in another home ....
Organized fa c ility ......................
Mother at work............................
14
31
7
22
13
11
16
24
6
22
23
8
17
23
5
20
28
6
20
24
5
18
23
9
The drop in care by nonrelatives in the child’s home is
confirmed by the household survey’s estimate of child care
workers in children’s homes. This estimate shows a 37-percent drop, representing a reduction of 200,000 workers from
1972 to 1993. The reduced use of child care workers in the
parents’ home is related to increasing demand for the ser
vices of centers, but the relationship between the two trends
is not clear. The greater availability of child care centers
may decrease the need for household workers. Alternately,
M onthly Labor Review August 1995
5
Em ploym ent in Day C are
household workers may be less desired by families than in
the past. Or, with much larger proportions of women enter
ing occupations in the executive, administrative, managerial,
and professional specialty categories,13 a smaller proportion
of women may be available for lower paying jobs, so house
hold help may be harder to find.
Factors relating to cost and convenience
After 13 years of fairly steady and strong growth, the number
of working mothers with children under age 6, and those of
children from 3 to 5, seems to have about leveled off in the
1990’s.14 But the number of day care workers continued to
increase about as steeply as ever. (See chart 1.) Contrasting
trends also occurred in an earlier period: from 1979 to 1982,
as the number of working mothers increased sharply, the
number of day care workers declined. These contrasts indi
cate that other factors have important effects on the number
of day care workers.
Certain developments have, in effect, lowered the price of
day care, making it more practical for some mothers of young
children to work outside the home. As a result, more young
mothers may have started working.15 In addition, among
working mothers and those who remain at home, these de
velopments also may have increased the popularity of day
care centers relative to other available child care arrange
ments.
Government funding. Several large Federal programs pay
billions of dollars for the care and education of young chil
dren outside the home, and in some large programs, the funds
have increased greatly in recent years. The four largest Fed
eral programs in this area totaled more than $5 billion in
fiscal year 1994.
Project Head Start is the most heavily funded of these pro
Table 1.
grams, with 1994 appropriations of $3.3 billion. Local em
ployment in Head Start is largely in the private sector be
cause the program funds local private organizations and lo
cal government agencies that perform the work. Head Start
is intended to provide comprehensive care for poor or dis
abled children. Although the project began in 1965, the Con
gress increased funding substantially in 1990 and continued
to increase it greatly in each subsequent year through 1994.
(See table 2.) Chart 2 compares the program’s appropria
tions with growth in private-sector child care jobs.
In addition to Head Start, Federal spending was increased
significantly for young children in 1990 when, for the first
time, comprehensive legislation regarding child care was
passed. As in Project Head Start, Federal funds in other major
programs are ultimately used to a great extent to pay for the
services of private child-care organizations. The Child Care
and Development Block Grant, which began in 1990, pro
vides funds to the States for care of the children of poor fami
lies and to improve the quality of care. Approximately $2.5
billion was appropriated for the first 3 years, and, in 1993,
the fiscal-year funding rose from $825 million to $893 mil
lion. Funding remained at that level in 1994.
The “At-Risk” Child Care Program also was created in
1990. It is designed to provide care for children of families
“at-risk” of becoming welfare recipients. States must pro
vide matching funds to receive Federal money, which so far
has been available at $300 million annually.
The Family Support Act Child Care Programs started
slightly earlier, in 1988. The Federal government distributes
money to the States to provide child care for the children of
parents receiving Aid to Families With Dependent Children
benefits and working, looking for work, or in approved edu
cation or training programs, as provided in the Job Opportu
nities and Basic Skills ( j o b s ) program. The Family Support
Act also provides funds for care of the children of parents
Selected factors affecting demand for day care, by age group
(In percent)
Age group
Under 3 ...........................................
3 to 5 .............................................
Under 6 ...........................................
6 to 9 ...............................................
Under 1 0 .........................................
Resident
U.S.
population,
1994
(thousands)’
11,705
11,906
23,611
14,975
38,586
Percent
growth in
population,
1972-94’
17.2
15.8
16.5
-3.0
8.2
’ Data are from the U.S. Bureau of the Census p p l -21 document.
2 Calculated from percentages In National Child Care Survey, 1990, p. 31,
and up-to-date population weights.
Calculated from percentages in preceding column and up-to-date popula
tion weights.
M onthly Labor Review A ugust 1995
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Use of
day care
centers
as primary
arrangement,
19902
(percent)
12.0
29.1
20.6
9.1
15.9
Mothers
who were em ployed4
Age group’s
enrollment as a
percentage of
total d ay care
enrollment, 19903
22
52
74
21
96
1975
28.3
539.6
33.2
49.0
558.3
52.3
—
—
—
—
* Data are from the Current Population Survey.
These mothers had no children under the age of 3.
N ote: Dash indicates data are not available.
1993
Employment in child day care services and related data
Year
Employment
in child day
care Industry
(thousands)
Population
under 6
years old
¿¿thousands)
Ratio of
em ployed
women to all
women
(percent)
Working mothers
of children
under 6
(thousands)
Working mothers
of children
under 6
(percent)
Enrollment in
Project Head Start
(thousands)
1972..................................
1973..................................
1974..................................
1975 ..................................
1976..................................
145.5
151.0
172.0
198.9
214.6
20,570
20,248
19,937
19,667
19,251
41.0
42.0
42.6
42.0
43.2
4,851
4,957
33
35
379
379
353
349
349
1977..................................
1978..................................
1979..................................
1980..................................
1981 ..................................
245.2
284.8
303.1
298.9
289.8
18,898
18,891
19,155
19,631
20,022
44.5
46.4
47.5
47.7
48.0
4,887
5,297
5,594
5,886
6,227
36
39
41
42
44
333
391
388
376
387
1982..................................
1983..................................
1984..................................
1985..................................
1986..................................
282.4
283.8
291.7
310.0
321.9
20,502
20,843
21,092
21,360
21,531
47.7
48.0
49.5
50.4
51.4
6,414
6,489
7,043
7,322
7,602
43
43
46
48
48
396
415
442
452
452
1987..................................
1988 ..................................
1989..................................
1990..................................
1991 .................................
333.4
356.3
378.4
391.4
417.2
21,662
21,822
22,067
22,528
22,897
52.5
53.4
54.3
54.3
53.7
8,137
8,104
8,478
8,732
8,758
51
51
53
54
53
447
448
451
541
583
1992..................................
1993..................................
1994..................................
450.8
473.4
501.9
23,224
23,479
23,611
53.8
54.1
—
8,662
8,764
—
53
53
—
621
714
—
N ote :
—
—
—
—
Dash indicates data are not available or are not comparable.
who have increased their earnings and have been able to leave
the a f d c program in the past year. Funds for these Family
Support Act programs nearly doubled from fiscal year 1992
to fiscal 1994, when $745 million was available.
In addition to Federal initiatives, State and local govern
ments provide many child care programs. The level of spend
ing per child varies greatly by State.16 In addition to pro
grams for poor children and others, State governments fre
quently fund onsite day care for the children of public em
ployees by setting up a private, not-for-profit corporation that
operates the center rent-free.17
As State governments receive more Federal funds, their
revenue may be made available for other purposes. Con
versely, when Federal aid to States and localities is cut, the
State or local government may find it necessary to reallocate
funds from another area of spending. The curve on chart 2,
which represents the number of employees in the day care
industry, shows a decline in the early 1980’s, when two re
cessions occurred, even though two other recessions, one in
the mid-1970’s and another in the early 1990’s, had no ap
parent effect on day care employment, which continued to
grow vigorously.
Federal outlays for education, training, employment, and
social services, adjusted for inflation, represents the first re
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lated statistic examined so far that may explain why em
ployment in the industry dropped in the early 1980’s but not
during the other recessions. As shown in chart 2, social
spending was cut deeply in Federal budgets in the early
1980’s, while this broad category of Federal spending de
clined less during the recession of the mid-1970’s and actu
ally increased during the 1990-91 recession. As increases
in such Federal spending occurred from 1975 to 1979 and
again from 1987 to 1993, day care expanded at a pace greater
than the growth rate in the number of children or of jobs
held by their mothers.
Tax breaks. In addition to explicit Federal spending, several
U.S. tax provisions help bring day care in reach of many
families. Perhaps the most important tax change was the
initiation and expansion of the Earned Income Credit, which
began in 1975 and was increased to a major extent in 1990
and again in 1993. Although a small amount of this credit
can be claimed by low-income taxpayers with no children, it
benefits primarily lower-income families with children. A
credit of up to about $2,500 goes to taxpayers with earnings
of $11,000 or less. The Earned Income Credit is different
among such credits because when the amount claimed by a
taxpayer exceeds the income tax liability, he or she is reimM onthly Labor Review August 1995
7
E m ploym ent in Day Care
bursed for the balance. The total amount claimed each year
under this credit has increased more than five-fold since
1975, even after inflation, partially because of numerous re
visions in the applicable tax rules, particularly in 1987, 1990,
and 1993. (See chart 2.)
While the credit does not specifically provide for day care,
the credit is often cited in literature concerning the financing
of the care of young children. Low-income families use day
care facilities; among children in families below the poverty
line in which the mother works, 18 percent attended orga
nized day care facilities in 1991.18
The Dependent Care Tax Credit benefits primarily a more
middle-income group of families; in 1992, this credit was
claimed to the greatest extent by families with incomes be
tween $20,000 and $50,000. The credit can be claimed for
expenses incurred for the care of dependents if the care is
necessary for the taxpayer to be employed. After adjustment
for inflation, the annual amount claimed by taxpayers about
tripled from 1976 to 1988 In 1988, tax law changes re
moved credit for the care of children over 13 and reduced the
amount of expenses that could be claimed; the aggregate an
nual amount claimed by taxpayers suddenly dropped and re
mained at roughly the same level through 1994, according to
projections. But the amount claimed in 1994 was still 85
percent above the 1976 level after adjustment for inflation.19
(See chart 2.)
Since 1981, certain employer-provided dependent care has
been excluded from an employee’s gross income for Federal
income tax purposes. Such dependent care may be provided
in the form of on-site or nearby child care facilities, reim
bursement of employees for child care expenses, or reimburse
ment accounts that are also usable for other nontaxable em
ployee benefits. Many employers offer such benefits; in 1993,
40 percent of full-time employees of medium and large pri
vate establishments were eligible for reimbursement accounts
that could be used for dependent care.20
Private initiatives. Corporate and nonprofit organizations
have made significant efforts to provide day care. The orga
nizations represent a diverse group, including major corpo
rations and religious and other nonprofit organizations.
Employers sometimes operate their own day care centers
for employees and in other cases contract with a for-profit or
nonprofit child care organization. In at least a few cases, the
service also is made available to nonemployee community
members. Other companies reimburse parents’ expenditures
on day care or arrange discounts. Consortiums of employ
ers, in some cases also including labor unions, have started
Employment in day care industry far outpaces factors influencing dem and for child care
(Percent change in employment In day care industry and in selected factors affecting demand for child care, 1975-94.)
Percent of
Percent of
0
1975
1977
0
1979
1981
1983
1985
1987
1989
1991
1994
NOTE: Shaded areas denote recession from peak to trough, as defined by the National Bureau of Economic Research Inc.
SOURCES: Current Employment Statistics program; Current Population Survey; and Bureau of the Census P-25 series of publications.
8 FRASER
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Digitized for
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day care centers that are located near several places of work.21
day care industry in which employment has grown even faster
than in the segments included in the establishment surveys.
Cost effects
From 1983 to 1993, the household survey measure of day
The average hourly pay in 1994 for production or care employment more than doubled, gaining 465,000 jobs,
nonsupervisory employees was $ 11.12 for the private sector and or 1 1 0 percent; the b l s establishment survey showed a gain
$6.83 in the day care industry. From 1972 to 1994, average of 67 percent during the period.
hourly pay of workers in the industry, excluding managers,
The household survey estimates of employees in the day
adjusted for inflation, declined by 10 percent.22 The cost of care industry include government employees, self-employed
labor in day care centers is relatively inexpensive and has workers, and private-sector wage and salary workers. (The
become less expensive over the years.
two surveys of employers include only private-sector wage
Despite the drop in real earnings of day care workers, the and salary workers.) Including these additional workers par
price of day care to consumers, as estimated in the consumer tially explains the differences in numbers of employees, but
price index, rose more rapidly than general inflation in the last the household survey’s estimates of private wage and salary
few years. An index of day care prices was first produced for a workers in the day care industry are larger and faster grow
complete year in 1990. From 1990 to 1994, day care prices ing than those of the b l s establishment survey.
rose by 20 percent while overall consumer prices for all urban
One reason for the differences in initial level and trend is
consumers rose by only 13 percent. Tax breaks and govern related to the surveys’ different methods of determining the
ment and private day care programs, which deliver care at a industry classification of workers. In the household survey,
below-market price as in Project Head Start, reduce costs to the classification is based on individuals’ descriptions of their
parents and partially account for the huge growth in day care workplaces. Many large employers in industries other than
use despite the relatively rapid inflation in the industry. The day care provide onsite centers as a convenience to their em
comparatively low cost of employing day care workers also ployees. The household survey assigns the day care workers
helps explain the rapid growth of jobs in the industry.
at such onsite centers to the day care industry if the workers
themselves describe their workplace as a day care center. In
Other surveys
the establishment survey, if the day care workers are directly
As previously mentioned, estimates of employment from the on the payroll of the main establishment, rather than that of
monthly b l s survey of employers are used in this article as a separate organization, they are assigned to the main indus
the primary measure of growth in employment. One advan try classification of the entire establishment.
tage of this series of estimates is its relatively long history,
The household survey also offers estimates of employment
starting in 1972 and continuing into mid-1995. Estimates by occupation, including child care workers outside of pri
from other relevant sources are available; in most cases, they vate households and, separately, child care workers in the
differ in their scope and trend.
child’s home. (These categories do not include all workers
The Bureau of the Census estimates employment by in who supervise pre-school children; many employees of cen
dustry, based on various Census Bureau sources.23 Day care ters are pre-kindergarten teachers, a category not distinguish
services were first estimated in this program in 1988, and able in the survey from kindergarten teachers and therefore
estimates for the industry have been produced up to reference not usable for our immediate purposes.) From 1972 to 1993,
year 1992. Census Bureau estimates, like those from the b l s individuals employed in the occupation of child care worker
survey of employers, are based on the definition of a day care not in the child’s residence increased from 358,000 to 1 mil
establishment quoted earlier and exclude Government estab lion. (The trends of child care workers employed in the
lishments from the sector. Over the 4-year span, this series, child’s home were discussed in an earlier section, in connec
like the b l s survey of employers, shows growth, but not as tion with changes in the family.)
much growth. Over the 1988-92 period, the Census Bureau
All the surveys show substantial increases in the day care
program indicates a gain of 55,000 employees, or 15 per center industry or portions of it. Rates of growth range from
cent; the b l s series shows an increase of 27 percent.
4 percent a year, in the case of the Census Bureau data, to 8
The Current Population Survey ( c p s ) 24 of households also percent a year in the case of the broad industry series from
estimates employment in the child day care industry, beginning the household survey. The b l s establishment survey’s indus
in 1983. However, the c p s (household survey) definition of try estimates, which are the primary source of employment
child day care is broader than that of the two employer data for purposes of this article, increased by 6 percent annu
(establishment) surveys. The initial level of employment from ally, on average, from 1972 to 1994.
the household survey was 418,000 in 1983, while the b l s
Outlook
establishment survey showed employment of 284,000.
The household survey apparently includes segments of the Recently, the population of children has not only increased
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M onthly Labor Review A ugust 1995
9
Em ploym ent in Day Care
Employment in day care industry far outpaces factors influencing dem and for child care.
(Percent change in employment in day care industry and in selected factors affecting demand for child care. 1975-94)
Percent of
Percent of
SOURCES: BLS Current Employment Statistics program and U.S. Department of Health and Human Services.
NOTE: Shaded areas denote recessions from peak to trough, as defined by the National Bureau of Economic Research Inc.
SOURCES: U.S. Office of Management and Budget and BLS Current Employment Statistics program.
Dollars, in minions,
Amounts claimed for Federal Earned Income tax credits
Dollars, in millions,
NOTES: Amounts for the Earned Income Credit are projected In 1992-96 and are preliminary in 1991. The Dependent Care Tax
Credit amounts for 1991 and 1992 are preliminary, and amounts for 1993 and 1994 are projected.
Dollars are deflated by the CPI-U, base period 1982-84.
SOURCE: Joint Congressional Committee on Taxation.
M onthly Labor Review August 1995
Digitized for10
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but also accelerated in growth. Although future trends of
most of the forces that have driven employment in the indus
try cannot be predicted with confidence, extensive popula
tion projections are available from the Bureau of the Census.
These projections show a pattern of deceleration followed by
decline in the population of young children:
Time period
Percent change in population
3 to 5 years old
1983-88 ............................
1988-93............................
1993-98............................
1998-2003..........................
6.2
7.7
4.8
-2 .9
Under 6 years old
4.7
7.6
.1
-2.1
As can be seen, the recent relatively strong gains in the
most relevant age groups are forecast to decelerate by 1998;
these populations will fall by 2003.
While final Federal budget figures for fiscal year 1996
and later are not yet available, increases in Federal child
care spending from 1994 to 1995 is expected to slow. Fed
eral child-care spending on certain major programs jumped
by 84 percent in 1991 after expansion of the jobs Child Care,
Transitional Child Care, and Head Start programs, and cre
ation of the “At-Risk” programs and the Child Care and De
velopment Block Grants. Since then, the combined funding
of these programs and Project Head Start has been increas
ing by about 20 percent annually. But in 1995, their com
bined funding is to grow by only 3 percent.
Amounts claimed under the Federal Earned Income Credit
are projected to grow vastly, by 89 percent, from 1993 to 1996.
But even this growth represents a slight deceleration, as the
amount claimed increased by 91 percent from 1990 to 1993.25
These developments suggest deceleration in day care em
ployment. The eventual decrease in the population of young
children suggests a greater deceleration or decline in em
ployment in the industry. Although the percentage of work
ing mothers of young children has leveled off in the last few
years, projections do not exist.
In s u m , the number of workers in the private day care indus
try has more than doubled since its employment was first
estimated in 1972, increasing by nearly 400,000 jobs. The
industry has been influenced by the increasing population of
children; the dramatically climbing percentage of job hold
ers among mothers of young children, and among other
women; Federal, State, and local government spending on
child care; increased Federal tax breaks for families with
children; and many private initiatives to provide needed day
care. But at least two of these factors will not continue to
increase so rapidly. Federal spending on certain major child
care programs is to decelerate from fiscal 1994 to fiscal 1995,
although it may possibly later accelerate. Growth in the U.S.
population of young children will decelerate in the next 5
years, and this population will start to decline by 2003. As a
result, the industry is unlikely to sustain the rapid growth it
has experienced since 1972.
□
Footnotes
1 See Howard V. Hayghe, “Are women leaving the labor force?” Monthly
Labor Review, July 1994, pp. 37-39.
2 Ellen Eliason Kisker, Sandra L. Hofferth, Deborah A. Phillips, and Eliza
beth Farquhar, A Profile of Child Care Settings: Early Education and Care in
1990 (Princeton, n j , Mathematica Policy Research, Inc., 1991), vol. I, p, 212.
3 Comparable estimates o f total enrollees in day care for considerably
separated points in time will soon be available. The National Center for
Education Statistics of the U.S. Department of Education is conducting the
1995 National Household Education Survey, which, like the 1991 and 1993
surveys o f that name, will generate an estimate of national enrollment in day
care, and many other statistics relevant to early learning.
4 Kisker, Hofferth, Phillips, and Farquhar, A Profile of Child Care Set
tings, vol. I, p. 208.
5 Sandra L. Hofferth, April Brayfield, Sharon Deich, and Pamela
Holcomb, National Child Care Survey, 1990 (Washington, The Urban Insti
tute Press, 1991), p. 31.
6 Population figures in this article are from the Bureau of the Census P-25
series o f publications and PPL-21.
7National Child Care Survey,
1990, p.29.
8 Statistics on working mothers in this article are from the Current Popu
lation Survey. Results for time periods after 1993 are not comparable to
earlier results because o f changes in methodology and population weights
used.
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9 Data from the Current Population Survey.
10 Donald J. Hernandez and David E. Myers, “Family Composition, Par
ents’ Work, and the Need for Child Care among Preschool Children: 19401987,” Paper presented at annual meeting of the Population Association o f
America, New Orleans, 1987, p. 5.
11 Data from the Current Population Survey. Data after 1993 are not
comparable to earlier data because o f changes in methodology and popula
tion weights.
12 Lynne M. Casper, Mary Hawkins, and Martin O ’Connell, Who’s Mind
ing the Kids? Child Care Arrangements, Fall 1991 (Washington, U.S. De
partment of Commerce, Bureau of the Census, 1994), pp. 6, 7.
13 From Current Population Survey data.
14 For further information, see Hayghe, “Are women leaving the labor
force?” pp. 37-39.
15 Jonathan R. Veum and Philip M. Gleason, “Child care: arrangements
and costs,” Monthly Labor Review, October 1991, p. 14.
16Information on Federal and other government programs from The State
of America’s Children Yearbook (Washington, Children’s Defense Fund, 1994),
pp. 29-32, The State of America’s Children 1992 (Children’s Defense Fund,
1992), pp. 15-22, and Child Care and Development Key Facts (Children’s
Defense Fund, 1994), pp. 13-17.
17 Barbara Adolph, “Work and family benefits come of age,” Government
M on th ly Labor Review August 1995
11
Em ploym ent in Day Care
Finance Review (October 1992), p. 46.
18 Casper, Hawkins, and O’Connell, Who ’s Minding the Kids? p. 14.
19 U.S. House Ways and Means Committee, Overview of Entitlement Pro
grams (Washington, U.S. Government Printing Office, 1994), pp. 705-7.
20Employee Benefits in Medium and Large Private Establishments, 1993,
Bulletin 2456 (Bureau o f Labor Statistics, November 1994), pp. 5-6.
21The State of America’s Children 1992, pp. 23, 24; Child Care and De
velopment Key Facts, pp. 17-19; and Barri Bronston, “Child Care is Part of
the Job,” The Times-Picayune (New Orleans, la , June 14, 1993), p. C l.
23County
Business Patterns, U .S. G overnm ent Printing O ffice,
Washington, annually.
24 The Current Population Survey produces estimates o f all civilian
employment and unemployment, and other demographic estimates, based
on a monthly survey o f 60,000 households. Results o f the survey appear in
Employment and Earnings. R esults for periods after 1993 are not
comparable to earlier results because o f changes in m ethodology and
population weights used.
25 Figures from U.S. House Ways and Means Committee, Overview of
Entitlement Programs (Washington, U.S. Government Printing O ffice,
1994), p. 704.
22From ces data.
Where are you publishing your research?
The Monthly Labor Review will consider for publication studies of the
labor force, labor-management relations, business conditions, industry
productivity, compensation, occupational safety and health, demographic
trends, and other economic developments. Papers should be factual and
analytical, not polemical in tone. Potential articles should be submitted to:
Editor-in-Chief, Monthly Labor Review, Bureau of Labor Statistics,
Washington, DC 20212-0001.
12
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Family Health C overage
Health insurance co verag e
for families with children
Findings from Consumer Expenditure Survey
show that families without health insurance
are less likely to receive some kinds of care
than families who are at least partially insured,
even when income and other characteristics are held constant
Geoffrey D. Paulin
and
Elizabeth M. Dietz
G eo ffrey D. Paulin is an
eco no m ist in th e
Division o f Consumer
Expenditure Surveys,
a n d Elizabeth M. Dietz
is an econom ist in th e
Division o f O c c u p a
tional Pay a n d
Em ployee Benefit
Levels, Bureau o f Labor
Statistics.
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Federal Reserve Bank of St. Louis
ealth insurance coverage is an impor
tant ingredient in the maintenance of
good health. This is particularly true for
families with children. According to Peter J.
Cunningham and Alan C. Monheit, children in
families without health insurance coverage are
“at a disadvantage regarding access to, quality
of, and continuity of health care.”1Judith D.
Kasper finds that uninsured children under 18
are less likely to see a physician at least once
during the past year, and are less likely to visit a
physician for an immunization or general check
up.2 Such regular, preventive medical care is es
pecially important for children who, in general,
are more prone to illness than adults. Without
preventive care, families may face large medical
expenses as their children grow up.
Additionally, health care costs have risen sub
stantially in recent years. Data from the Con
sumer Price Index show that the price of medi
cal care has risen at a much higher rate than for
all other goods and services. From 1989-94, the
medical care index increased 41.3 percent, com
pared with 18.2 percent for all items less medi
cal care. In 1993, the Nation’s health care costs
rose to $884.2 billion, up 7.8 percent from 1992.3
A recent article by Geoffrey D. Paulin and Wolf
D. Weber suggests that as a result of these large
increases, the direct costs of funding health care
have been shifting from business and govern
ment to families, thus affecting their expendi
tures for nonhealth items.4
Meanwhile, in 1992, more than 8 million
American children under age 18 had no health
H
insurance coverage of any kind.5 While many of
the poorest families receive health insurance in
the form of government-provided medicaid ben
efits6 the percentage of children without public
or private health insurance coverage grew by
more than 40 percent between 1977 and 1987.7
This study identifies families with children
that have full health insurance coverage, partial
coverage, and no coverage. It examines the de
mographic characteristics of each insurance
group, types of policies held, health care expen
diture patterns for each group, and the relation
ship between the family’s demographics and the
probability of being in a particular “coverage
group.”
Background. According to Gloria J. Bazzoli,8
studies examining the health insurance status of
individuals in an attempt to measure medical
indigence have generally defined medical indi
gence as the “lack of public or private health
insurance coverage. The rationale behind this
definition is that the uninsured are entirely re
sponsible for their own medical expenses. If they
experience a costly illness, they are less likely to
be able to afford necessary treatment than simi
larly ill individuals with insurance coverage.”9
Bazzoli also describes a study in which the au
thor examines “underinsurance,” a status that
“depends upon the probability that an individual
will experience large out-of-pocket expenses due
to a costly illness.”10
In a subsequent study, Richard D. Miller11
uses data from the 1987 Consumer Expenditure
M onthly Labor Review August 1995
13
Family Health C o ve ra g e
Interview Survey to identify medically uninsured consumer
units12 rather than uninsured individuals. Miller uses a bino
mial logit model to estimate the relationships between vari
ous independent variables and the probability that a family
has inadequate coverage—that is, the probability of having
at least one member of the consumer unit who lacks health
insurance coverage.
A later paper by Elizabeth M. Reise,13 which examines
only families with children, divides the sample into three
groups: those with full health insurance coverage (that is, all
members are covered), partial health insurance coverage
(that is, at least one, but not all, members are covered) and
no health insurance coverage (that is, no member is cov
ered). Reise uses an ordered multinomial logit to examine
the probability of being in each group. Reise’s paper is im
portant because it distinguishes between those families with
no (or at most very limited) health insurance coverage and
those families with at least some health insurance coverage.
These families have different spending patterns, as described
by Paulin and Weber.
This study builds upon and extends the works of Miller
and Reise in several ways. In addition to using more recent
data, this study, as noted earlier, describes types of policies
that families with insurance hold, as well as differences in
levels of health care expenditures for families with different
levels of coverage. It examines the probability of incurring
health care expenditures as well as the probability of being
insured.
The data. The data for this study are selected from the
1991-93 Consumer Expenditure Interview Surveys for fami
lies with all children under age 18.14 Families are defined as
consumer units consisting of a husband, wife, and their own
children with no other persons present, or single parents with
their own children and no other persons present.
Because the focus is on families who must rely on private
coverage, families covered by the medicaid and medicare
programs are excluded from the analysis. In addition to
health benefits, medicaid recipients may receive other ben
efits (such as food stamps) that would distort estimates of
the relationship between characteristics (such as income) and
the decision to purchase insurance. Similarly, virtually all
U.S. citizens who are at least 65 years old are eligible for
medicare, thus potentially distorting estimates of the rela
tionship between age and the decision to purchase insurance.
Additionally, the costs and benefits of enrolling in medicare
(once eligible) are assumed to be different from those of en
rolling solely in private insurance programs. Therefore,
medicare recipients are also excluded.15
Consumer Expenditure Survey collects information on the
number of family members covered by each policy. It does
not record specifically which members are covered by the
14
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policy. The difference between the number of family mem
bers and the number of members covered by a household
policy is used as a proxy to measure complete or incomplete
health insurance coverage. If the family holds more than one
policy, the total number of members covered by all policies
must be greater than or equal to the number of family mem
bers for the family to be considered fully covered. It is as
sumed that households do not overlap coverage for some
members while having no coverage for others. Policies for
persons outside the family, or that are limited in coverage
(dental only or special policies for injuries related to school
athletic programs) are counted as covering zero family mem
bers for the purpose of defining coverage status.
As in the studies by Miller and Reise, this analysis uses
data only from the second interview of the Consumer Ex
penditure Interview Survey. Consumer units are interviewed
five times on a quarterly basis. The selection of only secondinterview families avoids biasing the results by ensuring that
all families who are analyzed are unique.
All data presented in this study are unweighted to be con
sistent with those shown in the regression results. Logistic
regression is sensitive to weighting, as described later.
Demographic characteristics. Table 1 shows the differ
ences in demographic characteristics of families with chil
dren, by insurance coverage category. Although there is little
difference in age or family size for the groups, income (as
proxied here by total expenditure outlays16) appears to be
correlated with insurance status. The fully covered have the
highest incomes, while the uninsured have the lowest in
comes. Similarly, uninsured families have lower levels of
education, lower levels of work force participation and there
fore fewer earners than the insured families. Uninsured fami
lies are also more likely to be black or Hispanic17 than par
tially or fully insured families. The uninsured are the only
group whose families are about as likely to rent as to own
their homes, although the rate of “outright” homeownership
(that is, families that own with no mortgage) appears to be
highest for the uninsured.
Policies held. Table 2 shows that fully and partially in
sured families have similar types of policies. About the same
percentage in each group holds at least one Blue Cross/Blue
Shield policy, other commercial health policy, or dental only
policy. (However, the partially insured are less likely to be
members of a health maintenance organization— h m o — and
to have more limited coverage policies, as denoted by “other
health insurance.”) The average number of policies held is
also similar, though partially insured families have slightly
fewer on average. But the quality of the policies held is dif
ferent. Fully insured families on average cover 113 percent
of their members. Partially insured families, however, cover
Demographic characteristics of families with
children by health insurance status, Consumer
Expenditure Survey, 1991-93
Characteristic
Fully
insured
Sample size ................................
2,605
347
773
Characteristics of
average family
Age of reference person.........
Family s iz e ............................
Number of earners..................
Persons under
18 years old...........................
37.3
3.8
1.8
37.1
3.6
1.7
35.7
3.7
1.5
Partially
insured
Uninsured
1.9
1.9
2.0
Total expenditure
outlays (annual)
M ean...................................
Median.................................
$40,785
$34,741
$32,491
$28,686
$28,613
$24,277
Other characteristics (in percent):
Living in the—
Northeast............................
Midwest...............................
South...................................
W est....................................
Urban area..........................
22.8
28.6
27.2
21.5
87.8
16.7
24.2
36.3
22.8
87.3
14.8
19.3
35.5
30.5
89.0
Black.........................................
Hispanic....................................
7.0
4.7
7.8
8.7
10.9
15.3
Occupation of the
reference person:
Wage and salary.................
Manager/professional.......
Technical/sales.................
Service..............................
Blue collar.........................
Self-employed.....................
Retired.................................
Unemployed........................
Out of the labor force..........
88.2
39.0
18.4
5.9
24.9
7.0
.3
.4
4.1
87.6
30.6
23.9
11.2
21.9
6.6
.3
.3
5.2
75.9
23.3
15.1
10.1
27.4
10.5
.3
1.3
12.0
Education of the
reference person:
Less than high school.........
High school graduate/
some college.....................
College graduate.................
7.0
10.7
22.7
58.7
34.3
65.4
23.9
57.2
20.2
Family composition:
Single parent.......................
Husband/wife family............
12.6
87.4
30.0
70.0
22.5
77.5
Earner status:
No earners..........................
One earner..........................
Two earners........................
At least three earners.........
0.8
30.9
60.8
7.5
1.4
39.2
51.6
7.8
6.9
44.1
43.3
5.7
Housing tenure:
Homeowner with mortgage..
Homeowner, no mortgage ...
Renter.................................
68.9
7.8
23.3
54.8
6.9
38.3
41.5
9.3
49.2
At least one child:
Under age 6 .............................
6 to 11 ..................................
12 to 1 7 ...............................
50.6
51.3
37.7
47.3
43.5
42.1
47.6
53.6
41.3
Student status of
reference person:
Full tim e...............................
Part tim e..............................
1.4
5.5
3.8
4.6
2.2
4.9
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50 percent of their members. Although partially insured
families are more likely to have at least one policy fully paid
for by someone outside the family (such as an employer),
fully insured families are more likely to have at least one
partially paid policy, and partially insured families are more
likely to have at least one policy for which they pay entirely.
Children make up a large percentage of individuals not
covered in partially insured families. Although the Consumer
Expenditure Survey does not ask which members are cov
ered by each policy, under the assumption made earlier that
families do not overlap coverage as long as at least one
member remains uncovered, a lower and upper bound on the
number of children covered can be estimated. To get the lower
bound, all families are assumed to follow an “adult first”
strategy. That is, the first person covered will be an adult. If
the family is a husband/wife family, then if only two mem
bers are covered, they will be the husband and the wife. Only
if three members are covered will a child be covered. To get
the upper bound, families are assumed to follow a “child
first” strategy. That is, only after all children are covered
will an adult be covered. As shown in the following tabula
tion, the average partially insured family, which has 1.9 chil
dren, has between 0.5 children and 1.5 children covered:
Number of children............................
1.9
Number o f children covered:
Adults first...........................................
Children first.......................................
0.5
1.5
Percent of children covered:
Adults first...........................................
Children first.......................................
26.3
78.9
In other words, about one-fourth to three-fourths of chil
dren are covered in partially insured families. This implies
that at least one-fourth of all children in partially insured
families have no health insurance coverage. If combined with
children in uninsured families, this implies that between oneninth and one-sixth of the children in the sample lack health
insurance coverage.18
Health care expenditures. Table 3 shows that the fully in
sured pay the largest amount for health care in total. Al
though partially insured families appear to pay slightly more
for medical services than fully insured families, this differ
ence is not statistically significant.19
When shares of the health care budget are considered, the
fully insured spend the largest share (49 percent) on health
insurance, but the smallest on medical services (39 percent).
However, the fully and partially insured spend about the same
share (12 percent) on prescription drugs. The uninsured
spend the largest shares on medical services (57 percent)
and prescription drugs and medical supplies (15 percent) and
the smallest share for insurance (28 percent).
M onthly Labor Review August 1995
15
Family Health C o ve ra g e
However, insurance premium payments for the uninsured
could be for someone outside the immediate family (perhaps
an older relative, a child from a previous marriage, and so
forth), and therefore perhaps should not be counted when
comparing health care expenditures by insurance status.
Furthermore, insurance policies may “favor” certain types
of treatment—that is, they may pay for medical services, but
not prescription drugs. Therefore, it is interesting to exam
ine health care expenditures for items other than insurance
premiums to see how levels and shares differ by insurance
status. Of the health care dollars not spent on insurance pre
miums, the fully insured allocate 76 percent to medical ser
vices and 24 percent to prescription drugs and medical sup
plies. This compares with an 81 -percent/ 19-percent split for
the partially insured, and a 79-percent/21-percent split for
the uninsured.
Probability of purchase. The fact that the fully and partially
insured families spend more on medical services, prescrip
tion drugs, and medical supplies does not, by itself, indicate
that insurance status is related to health care usage. The un
insured have lower incomes than the insured, so it is to be
expected that they spend less on these services. Therefore, to
estimate the direct effect of health insurance status, all other
factors, such as income, age, and family size must be held
constant. Rose M. Rubin and Kenneth Koelln perform such a
study.20 They find that indeed, ceteris paribus, the presence
of insurance is positively correlated with expenditures for
medical services, prescription drugs, and medical supplies.
However, Rubin and Koelln do not measure frequency of
usage of these goods and services. This may be because the
Consumer Expenditure Survey does not measure usage di
rectly; that is, the respondent is not asked how many times a
member of the family went to the doctor during the past 3
months. However, if a respondent reports a medical expen
diture, then someone in the family must have used such
services.
Results of a logistic regression modeling the probability
of incurring expenditures for different types of health care
are shown in table 4 (medical services) and table 5 (pre
scription drugs and medical supplies). In this case, the lo
gistic regression is binomial, meaning that the outcome pre
dicted is either “yes” (family did incur an expenditure) or
“no” (family did not incur an expenditure). The predicted
probability of incurring an expenditure is:
P= i/{ l +exp[-i *(a + p'x]}
where
P is predicted probability of incurring an expenditure
a is a constant
p is a vector of parameter estimates
X is a vector of independent variables.
16
Monthly Labor Review August 1996
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In tables 4 and 5, parameter estimates for the first column
represent the coefficients for the fully insured. If statistically
significant, these indicate that the variable is important in
predicting the probability of incurring an expenditure for
medical services (table 4) or prescription drugs (table 5).
The second and third columns of parameter estimates show
whether the relationship of the variable to the probability
of incurring an expenditure is different for the partially in
sured or uninsured than it is for the fully insured. If the pa
rameter estimate is statistically significant, the relationship
is different.
As with any regression, it is important to define a refer
ence group to make comparisons more accurate. In tables 4
and 5, each insurance group consists of families with median
income (table 1), whose reference person is between 25 and
44 years old, married with two children, neither black nor
Hispanic, and containing two earners.21 The probability of
incurring an expenditure for each of these groups is shown in
the tables. (For example, table 4 shows that members of the
fully insured reference group are predicted to have a 73.2percent probability of incurring expenditures for prescription
drugs and medical supplies, compared with a 66.1-percent
probability for members of the uninsured reference group.)
H<»nlth in s u rn n c e p o licies, by health insurance
coverage status, 199 1-93
Characteristic
Fully
insured
Partially
insured
Uninsured
Family size.....................................
Members covered....................
Percent of members covered....
3.8
4.3
113.1
3.6
1.8
50.0
3.7
.0
.0
Percent with at least one—
Blue Cross policy.....................
Commercial health policy.........
HMO policy...............................
Dental only policy.....................
Other health Insurance policies1
28.1
47.8
24.1
9.3
13.6
28.5
44.7
18.4
8.7
19.0
9.2
13.7
8.9
7.0
4.4
Average number of policies held ....
Blue Cross................................
Commercial health....................
HMO..........................................
Dental on ly................................
Other health insurance1 ..............
1.39
.31
.56
.26
.10
16
1.32
.30
.50
.21
.09
.22
.45
.09
.15
.09
.07
.05
Percent with at least
one policy paid for—
Entirely by the family..................
Partially by someone else..........
Entirely by someone else...........
18.6
56.2
39.9
22.8
45.0
45.5
8.7
18.5
11.9
Number of policies paid for—
Entirely by the family..................
Partially by someone else..........
Entirely by someone else...........
.22
.68
.49
.29
.52
.50
.27
.60
.40
1 Includes policies providing special limited coverage, medicare supple
ments, and other health Insurance policies.
Health care expenditures by health insurance
coverage status, 1991-93
Expenditure allocation
Total health care (annual)................
Health insurance..........................
Medical services.....................
Prescription drugs/
medical supplies......................
Fully
insured
Partially
insured
Uninsured
$1,880
920
732
$1,668
663
811
$972
269
556
229
194
147
Percent of health care
allocated to— .............................
Health insurance.........................
Medical services........................
Prescription drugs/
medical supplies.........................
100.0
48.9
38.9
100.0
39.7
48.6
100.0
27.6
57.2
12.2
11.6
15.1
Percent of total expenditure
outlays allocated to—
Health insurance.......................
Medical services..........................
Prescription drugs/
medical supplies.......................
2.3
1.8
2.0
2.5
.9
1.9
.6
.6
.5
67.3
70.1
58.8
62.0
23.0
51.2
57.7
54.2
40.5
Percent reporting expenditures
(quarterly):1
Health insurance........................
Medical services........................
Prescription drugs/
medical supplies.....................
1 Does not include reimbursements for payments made in previous
quarters but received in current quarter.
In tables 4 and 5, probabilities for each group are pre
dicted, given that each reference group family has $32,175
in total expenditure outlays, which is the median value for
the sample as a whole. This value is substantially less than
the median value for the fully insured (about $2,000 less),
and substantially more than the median values for the par
tially insured (about $6,500 more) and uninsured (about
$7,800 more).
Table 4 shows that insurance status is definitely impor
tant for the reference group. The fully and partially insured
have similar probabilities of incurring a medical service ex
penditure. However, when the probability for the fully in
sured (73.2 percent) is compared with the probability for the
uninsured (66.1 percent), the difference is significant in a
statistical and economic sense.
Thus, the data may indicate that uninsured families are
less likely to seek preventative care, as Kasper finds. By con
trast, families with insurance may be more likely to visit the
doctor for minor illnesses, as Rubin and Koelln imply. To
further investigate the “usage” issue, expenditures for pre
scription drugs and medical supplies are examined. A fam
ily with insurance may automatically incur an expenditure
for a doctor visit (either through a deductible or copayment).
However, if the illness is not severe, the doctor need not pre
scribe medicine. If insured families are more likely ceteris
paribus to incur prescription drug expenditures, then it is
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safe to assume that when they become ill, they become well
faster than their uninsured counterparts. Furthermore, any
reimbursements for these expenditures are treated as if no
visit occurred, because the reimbursed visit may have taken
place more than 3 months prior to the interview date.
When all characteristics, including income, are held con
stant, the predicted probabilities that the fully and partially
insured will incur an expenditure are once again very simi
lar: 58 percent for the fully insured and 61 percent for the
partially insured (table 5). The predicted probability for the
uninsured, 47 percent, suggests that this group is much less
likely to incur an expenditure for prescription drugs or medi
cal supplies than either of the insured groups, even when all
else is held constant. However, because rieither the intercept
nor income parameter estimate is statistically significant,
caution must be used when interpreting this result.
Given the findings of Kasper, those of Rubin and Koelln,
and the results shown in tables 4 and 5, it appears that there
is a relationship between level of insurance coverage and
receipt of medical care. Therefore, it is important to under
stand the relationship between demographic characteristics
and level of insurance coverage.
Probability of coverage. To estimate the relationship be
tween level of health insurance coverage and demographic
variables, a different kind of logistic regression is needed. In
this case, there are three possible outcomes: full health in
surance coverage, partial health insurance coverage, or no
health insurance coverage. Therefore, the dependent value
can take on values from 1 (fully insured) to 3 (uninsured).
Because the dependent variable takes on three distinct, quali
tative values of ascending order, the parameters of this model
are estimated using an ordered multinomial logistic regres
sion. From these estimated parameters the probabilities that
a particular family will be fully, partially, or not insured can
be predicted using the following formulas:22
p„
= F(P'x)
= F(P'X+a,) - F(P’x)
Pm-2
= F(P'x + a, + a 2) - F (px + a ,)
where
Pmis the probability of being fully insured (in this case)
Pml is the probability of being partially insured
Pm2 is the probability of being uninsured.
The function F () has the same form as it does for a bino
mial logit. For example,
F(P'x) = 1/[1 + exp(-l * P'jc)]
where
fV is a vector of parameter estimates
* is a vector of demographic characteristics.
M onthly Labor Review August 1995
17
Family Health C o vera ge
Several independent variables are chosen for this model.
The first is annual total expenditure outlays for the family
(that is, quarterly total expenditure outlays multiplied by
four), which are used as a proxy for permanent income in
accordance with Milton Friedman’s “permanent income hy
pothesis.”23 Before using this variable, though, it is subjected
to a Box-Cox transformation to normalize its distribution.24
The formula for a Box-Cox transformation is:
Y* = (Y M )/^
where
Y is the initial value of total expendi
ture outlays
X is a variable found through experi
mentation
Y* is the transformed value of total
expenditures.
Using a maximum-likelihood tech
nique described by Stuart Scott and
Daniel J. Rope,25 the best estimate of X is
1/8.26 (This transformation of total ex
penditure outlays is also used in the bi
nomial logit described earlier.) In addi
tion to normalizing the distribution of
total expenditure outlays, the fact that X
is 1/8 is consistent with the assumption
that the probability of a family having
full health insurance coverage increases
with income, but at a decreasing rate.
This is a plausible assumption, as it in
dicates that an increase in income (say,
$1,000) is associated with an increase in
probability of having full coverage, but
that the increase in probability is greater
for a low-income family than for a highincome family receiving the same in
crease in income.27
Also included are several dummy
variables describing characteristics of the
reference person including age (under 25
or at least 45), ethnic origin (black or
Hispanic), type of occupation or labor
force status (if not working), level of edu
cation, and student status (enrolled in
college full time or part time). Dummy
variables describing the family include
number of children (one child or three
or more), type of family (single parent or
husband/wife), children’s age (at least
one child is older than age 12 because
older children may be less prone to ill
M onthly Labor Review August 1995
Digitized for18
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lU d iM
ness than younger children), region of residence (Northeast,
Midwest, or West),28 whether the family lives in an urban or
rural area, number of earners (no earners, one earner, or at
least three earners), and housing tenure (owner without mort
gage or renter).29 The omitted category in each case is shown
in table 6 with the regression results. The variables are meant
to control for differences in “tastes” for insurance (family
type, ethnic origin, education); opportunity of obtaining poli
cies (occupation, number of earners, and student status, be
cause some colleges and universities offer special policies to
students); and other factors.
Results of bine mial logit predicting probability of incurring expenditures
for medical se rvices, with median income held constant for all insurance
groups ($32,1 j'5)
Characteristic
Parameter
estimate
Estimate
Estimate
1
2
Reference group:....................
(1)
0
(1)
Intercept..................................
Standard error.....................
2-3.420
.587
-2.712
1.725
3-2.050
1.135
Annual expenditure outlays
(Box-Cox) .............................
Standard error.....................
2.208
.027
3.134
.080
Reference person under
age 2 5 ...............................
Standard error.....................
-.351
.285
Reference person over
age 4 4 ...............................
Standard error.....................
Fully
insured
0.732
Partially
Uninsured
insured
0.759
0.661
—
—
—
—
—
—
.081
.053
.737
.766
.669
—
—
—
.648
.629
-.024
.449
.658
.809
—
—
.573
—
.007
.129
-.076
.381
-.304
.273
.734
.747
.592
—
—
—
Number of children (two)
One child.............................
Standard error.....................
2-.233
.101
.376
.297
2.457
.213
.684
.785
.710
—
—
—
Three or more children.......
Standard error.....................
.058
.123
.104
.380
-.067
.245
.743
—
.788
—
.659
—
Family type (husband/wlfe)
Single parent.......................
Standard error.....................
-.058
.148
.402
.352
-.204
.276
.721
—
.817
—
.601
—
Ethnic origin (whlte/other)
B lack...................................
Standard error.....................
2-.708
.163
.060
.473
-.033
.318
.574
—
.623
—
.505
—
Standard error.....................
2 -.523
.194
-.421
.457
-.154
.301
.619
—
.551
—
.498
—
Number of earners
(one earner)
No earners..........................
Standard error.....................
-.487
.432
(4)
(1)
-.416
.313
-.731
.628
.627
—
.660
—
.366
—
-.111
.213
.732
—
.675
—
.636
—
.231
.184
.286
.396
.679
—
.755
—
.668
—
Age of reference person
(ages 25 to 44)
Hispanic.................................
One earner.......................... -1.39E-03
Standard error..................... 1.09E-01
At least three earners.........
Standard error.....................
-.257
.175
1 Not applicable.
2 Statistically significant at the 95-percent confidence level.
3 Statistically significant at the 90-percent confidence level.
4 Variable omitted from regression. None of the five families in this category incurred a medical service
expenditure.
Table 5.
Results of binomial logit predicting probability of incurring expenditures
for prescription drugs and medical supplies, with median income held
constant for all insurance groups ($32,175)
Characteristic
Reference group:....................
Intercept..................................
Standard error.....................
Parameter
estimate
(’>
2 -3 060
Estimate
1
Estimate
2
(')
(’>
1 055
1.064
Fully
Insured
Partially
Uninsured
Insured
0.584
0.606
0.468
.528
1 fin^;
1.579
Annual expenditure outlays
(Box-Cox).............................
Standard error.....................
2.160
024
.080
.073
.028
.049
.589
.612
.473
Age of reference person
(ages 25 to 44)
Reference person under 25.
Standard error.....................
-.135
.285
-.118
.609
.698
.437
.551
.544
.607
Reference person over
age 4 4 ...............................
Standard error.....................
.098
119
-.018
.357
.181
.260
.608
.625
.538
Number of children (two)
One child.............................
Standard error...................
-.070
093
.083
?78
.256
206
.567
.609
.515
Three or more children.......
Standard error.....................
.158
.112
-.047
.344
.135
.235
.622
.632
.541
Family type (husband/wife)
Single parent.......................
Standard error..................... .
.152
.141
-.178
.336
3 -.459
.621
.599
.393
Ethnic origin (white/other)
Black..............................
Standard error......................
3-.264
.161
-.424
.471
-.042
.314
.519
.436
.307
Hispanic..............................
Standard error.....................
2 -.976
.199
3.756
.446
.201
.315
.346
.552
.288
Number of earners
(One earner)
No earners...........................
Standard error.....................
3-.922
.501
1.067
1.136
.096
.664
.359
.640
.278
One earner...........................
Standard error......................
2-.229
.099
.031
.301
.099
.204
.528
At least three earners..........
Standard error.....................
3.300
.170
-.580
.475
-.227
.381
.655
.273
—
—
—
—
—
—
—
Not applicable.
Statistically significant at the 95-percent confidence level.
Statistically significant at the 90-percent confidence level.
For the sample as a whole, the median value for annual
total expenditure outlays is $32,175; the average age of the
reference person is 36.9, with average family size of 3.8 per
sons. Therefore, the reference group consists of husband/wife
families with two children (both under age 12), median out
lays,30 and two earners, whose reference person is between
ages 25 and 44, neither black nor Hispanic, working for a
wage or salary in a managerial or professional position, a
high school (but not college) graduate, and not enrolled in
college at present. These families live in homes they own
(though they still pay a mortgage) in the urban South.
The data used in this analysis are unweighted. As noted
earlier, logistic regression can be sensitive to weighting. If
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weighted, the parameter estimates tend
to be statistically significant in every case.
On the other hand, the relatively small
sample size (especially for the partially
insured and uninsured), may lead to large
standard errors for some parameter esti
mates, thus understating the number of
significant relationships. Therefore, in
the interest of obtaining conservative es
timates of statistical significance, no
weights are applied, but the 90-percent
confidence level is used to define statis
tical significance.
Regression results are shown in table
6. Along with coefficients, the predicted
difference in probability for each group,
com pared to the reference group is
shown. For example, families whose ref
erence person is under age 25, but who
are otherwise identical to the reference
group, are about 7 percent less likely to
have full coverage than families in the
reference group. Thus, for the younger
group, the value listed in the fully insured
column is -0.074. The younger group has
a 5-percent greater probability of being
uninsured. Thus, for the uninsured col
umn, the value is shown as 0.053.
Income and insurance status. Perhaps
the most important independent variable
.557
.436
in any study of consumer expenditure
patterns
is income. Generally, the more
.537
.486
income a family has, the more of any
good or service it can afford to purchase,
including health insurance. Therefore, it
is not surprising that the parameter esti
mate for income is statistically signifi
cant at the 99.9 percent confidence level.
However, despite the statistical strength of the relation
ship, the probability that a family has full insurance cover
age increases slowly with income. Table 7 shows how the
predicted probability changes if a family with characteris
tics of the reference group somehow obtains additional in
come. Given a 1-percent increase in income, the probability
of being fully insured barely increases—rising from 76.7 per
cent to 76.9 percent. The table shows that even with fairly
large increases of income (up to $3,000 per year, nearly a
10-percent increase), the probability of full coverage does
not increase much, rising only to 78.1 percent.
Nevertheless, because three-fourths of the reference group
are predicted to have full coverage, and well over four-fifths
M onthly Labor Review August 1995
19
Family Health C o ve ra g e
are predicted to have at least partial cov
erage, the reference group is predicted
to be relatively well-off when it comes to
insurance coverage. Therefore, it may be
more interesting to study those who are
least well-off: the uninsured.
Table 8 shows the predicted probabili
ties of coverage for a family with char
acteristics typical of the uninsured. That
is, the family is similar to the reference
group, except that it has substantially
lower income ($24,277, the median value
for the uninsured), rents its home, has a
reference person who is employed in a
blue-collar job, and one earner (the ref
erence person in this case).
Uninsured families are similarly slow
to purchase health insurance when they
receive increases in income. For ex
ample, an increase of $3,000 dollars (a
12-percent increase in income) is asso
ciated with a higher probability of full
coverage for families with characteris
tics typical of the uninsured; however,
the difference is small— 52.6 percent,
compared with 50.2 percent.
Other characteristics. Other demo
graphic characteristics are also associ
ated with differences in insurance cov
erage. Families with young parents (that
is those whose reference person is under
age 25) are significantly less likely to
have full coverage than older families.
On the other hand, families with young
children (all children are under age 12)
are more likely to have health coverage
than families who have at least one child
over age 12. Families may choose health
insurance coverage more readily when
the perceived health risks to their chil
dren are greater, during the years of early
childhood development. Families with
older children may also experience the
financial pressure of putting extra sav
ings into a college fund and may choose
not to spend on health insurance as a
result.
Educational attainment also raises the
probability of full coverage. Those who
did not graduate from high school
are less likely to be fully covered than
20
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P“ ™
* "
P re d ic te d p ro b a b ilitie s fo r in s u ra n c e status, m u ltin o m ia l lo g it results
Probability of being—
Parameter
Characteristic
Fully
Partially
Uninsured
estimate
insured
insured
Sample (size: 3,725)............................
—
0.699
0.093
0.208
Reference group:...................................
Intercept 1 ..............................................
Standard e rro r....................................
—
1-3.743
.569
.757
—
—
.153
—
—
Intercept 2 ..............................................
Standard e rro r....................................
’-3.160
.568
—
.090
—
—
—
—
Annual outlays (Box-Cox) .....................
Standard e rro r....................................
’ .232
.025
2.005
—
2-.001
—
2-.003
—
—
_
—
J Difference from reference group probability |
Age of reference person (25 to 44)
Reference person under age 2 5 ........
Standard e rro r....................................
3-.381
.199
-.074
—
.021
—
.053
—
Reference person at least age 4 5 ......
Standard e rro r....................................
.042
.120
.007
—
-.002
—
-.005
—
Number of children (two children)
One c h ild ............................................
Standard e rro r....................................
.129
.089
.022
—
-.007
—
-.015
—
Three or more children......................
Standard e rro r....................................
.061
.103
.011
—
-.003
—
-.007
—
Family type (husband/wife)
Single parent.......................................
Standard e rro r....................................
.083
.125
.014
—
-.005
—
-.010
—
Ethnic origin (white/other)
Black...................................................
Standard e rro r....................................
.121
.140
.021
—
-.007
—
-.014
—
-.081
—
.023
—
.058
—
Hispanic..............................................
Standard e rro r....................................
’-.412
.140-
Occupation (manager/professional)
Technlcal/sales...................................
Standard e rro r....................................
-6.20E-04
.117
-.000
—
.000
—
.000
—
Blue collar...........................................
Standard e rro r....................................
-.052
.113
-.009
—
.003
—
.007
—
Service...............................................
Standard e rro r....................................
’-.348
.152
-.068
—
.019
—
.048
—
Self-employed.....................................
Standard e rro r....................................
’-.717
.147
-.150
—
.038
—
.112
—
Retired................................................
Standard e rro r....................................
1.185
.748
.147
—
-.052
—
-.095
—
Unemployed.......................................
Standard e rro r....................................
-.210
.483
-.039
—
.012
—
.028
—
Out of labor force...............................
Standard e rro r....................................
-.238
.196
-.045
—
.013
—
.032
—
Education (high school/some college)
Did not graduate high school.............
Standard e rro r....................................
’-.525
.120
-.106
—
.029
—
.077
—
College graduate................................
Standard e rro r....................................
.012
.101
.002
—
-.001
—
-.001
—
At least one child over age 12............
Standard e rro r....................................
’-.258
.090
-.049
—
.014
—
.035
—
Region (South)
Northeast............................................
Standard e rro r....................................
'.648
.113
.095
—
-.032
—
-.063
—
Midwest..............................................
Standard e rro r....................................
W est...................................................
’ .633
.104
-.044
.094
—
-.008
-.032
—
.002
-.062
—
Age of children (all under age 12)
.005
C ultural differences by race and
ethnicity may make certain groups less
averse to the risk of being uninsured. Al
Parameter
Fully
Partially
Characteristic
Uninsured
insured
estimate
insured
though the coefficient for black families
is not statistically significant, the coeffi
Degree urbanization (urban)
R ural..................................................
0.188
0.032
-0.010
-0.022
cient for Hispanics is very significant. Its
Standard error....................................
—
—
_
.123
negative sign indicates Hispanic families
Number of earners (two earners)
No earners.........................................
1-1 .266
-.285
are less likely to be insured.
.055
.230
Standard error..................................
—
—
.339
Regional differences are significantly
One earner........................................
’-.368
-.072
.020
.052
related to differences in health insurance
Standard error....................................
—
—
.097
At least three earners........................
coverage. Compared with the South,
-.216
-.041
.012
.029
Standard error....................................
—
_
.163
which is the most populous region, fami
Housing tenure (owner with mortgage)
lies in the Northeast and Midwest have a
Owner, no mortgage..........................
-.199
-.037
.011
.026
Standard error....................................
—
—
.143
much higher probability of being fully
Renter............................................
'-.531
-.107
.029
.078
insured. This may be attributed to any
_
Standard error...................................
—
_
.091
number of factors, including differences
Student status (nonstudent)
Full-time..........................................
-.260
-.049
.014
.035
by region in State laws, costs of health
Standard error..................................
—
—
.266
care,
unionization of the work force
Part-time.............................................
.025
.004
-.001
-.003
Standard error...................................
.172
(which may result in greater availability
—
of employer-provided health plans), rates
1 Statistically significant at the 95-percent confidence level.
2 Difference in predicted probability given $1,000 increase in annual outlays.
at which employers offer benefits, or
3 Statistically significant at the 90-percent confidence level.
other factors. The West, however, is not
significantly different from the South.
those who did graduate, although there is no statistically sig
In most cases, the probability of be
nificant difference in probability of full coverage for high
ing partially insured does not change much with character
school and college graduates.
istics. This may imply that families “vault over” the par
Occupational status appears to be associated with differ
tially insured category—that is, if they get extra income, they
ent levels of health insurance coverage. The reference group
will move from no insurance to full coverage. But this is not
consists of salaried professional or managerial workers; these
necessarily true in all cases. For example, it is possible that
are the workers who are expected to have high-coverage
a two-eamer family with full insurance coverage moves to
health benefit plans. However, of the wage or salary occupa
the partial coverage class if an earner loses a job, rather than
tions, only those families whose reference person is employed
slipping all the way into no coverage. Some of those with
in services have a lower probability of being fully insured
partial coverage may move to the no coverage category
than members of the reference group. Families whose refer
under similar circumstances. Thus, the probability of par
ence person is self-employed are even less likely to have full
tial coverage is similar across demographic characteristics,
coverage.31
even though some families may be moving in and out of the
As expected, number of earners in the family is signifi
category.
cantly related to the level of health insurance coverage. Fami
lies with two earners (the reference group) are expected to
have more health coverage on average than families with
Predicted probability of health insurance status for
fewer earners but equal income, because the two-earner fam
families with median income ($32,175)
ily may have a choice between two employer-sponsored
Probability of being—
health insurance plans. (Or at least there is a greater chance
Item
Fully
Partially
that someone in the family is eligible for such a plan.) Fami
Uninsured
insured
insured
lies with more than two paychecks may need several incomes
At present level
to cover the family’s expenses. If all members earn relatively
of incom e.....................................
0.767
0.088
0.145
low wages, they may be in jobs which have poor benefits.
Given an increase in
Therefore, families with more than two earners are expected
income of—
to have a lower probability of full coverage. The negative
One pe rcent............................
0.769
0.087
0.144
$1,000 ..................................
0.772
0.086
0.142
coefficient for multiple earner families seems to confirm this
$2,000 ..................................
0.776
0.085
0.139
intuition, but it is not statistically significant. Therefore, no
$3,000 ..................................
0.781
0.084
0.136
firm inference can be drawn.
1 0 2139
Continued— Predicted probabilities for insurance status, multinomial
logit results
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Monthly Labor Review August 1995
21
Family Health C o vera ge
e a l t h in s u r a n c e status plays an important role in provid
ing health care to families. This study finds that families
with children and at least partial coverage are more likely to
receive at least some kinds of care (medical services) than
uninsured families with children, even when income and
other characteristics are equal.
Certain characteristics are related to the ability to obtain
health insurance coverage. In this study, income, age, edu
cation and number of earners are found to be positively re
lated to a family’s level of health insurance coverage. Char
acteristics of the reference person such as being a service
worker, self-employed, or Hispanic are negatively related to
the probability of coverage.
Although income is an important predictor of insurance
status, families do not change their level of coverage much,
even when income increases substantially. This would indi
cate that if increased health insurance coverage is a desired
outcome, direct grants of cash to families will not raise lev
els of coverage in any substantial way. Although prices
and qualities of insurance plans are not studied in this ar
ticle it would be useful to find out what influence these fac-
H
Predicted probability of health insurance status for
families with characteristics typical of the unin
sured (median income: $24,277)
Probability of being—
Item
Fully
insured
Partially
insured
Uninsured
At present level
of income...................................
0.502
0.142
0.357
Given an increase in
income of—
One percent...........................
$1,000 ................................
$2,000 ................................
$3,000 ................................
0.504
0.510
0.518
0.526
0.141
0.141
0.140
0.139
0.355
0.349
0.342
0.335
tors have on the probability of receiving coverage. Also, data
on difficulty of obtaining access to health insurance cover
age is useful to understanding why some families are unin
sured. For example, if plans are readily available through an
employer, are families likely to take advantage of them?32
Exploration of these issues should provide for interesting
future research.
□
Footnotes
1 Peter J. Cunningham and Alan C. Monheit, “Insuring the Children: A
Decade o f Change,” Health Affairs, Winter 1990, p. 78.
2 Judith D. Kasper, “The Importance o f Type of Usual Source o f Care for
Children’s Physician Access and Expenditures,” Medical Care, May 1987,
25(5), pp. 386-98, especially tables 4 and 7.
3HHS News, U.S. Department o f Health and Human Services, November
1994, p .l.
4 Geoffrey D. Paulin, and Wolf D. Weber, “The effects of health insurance
on consumer spending.” Monthly Labor Review, March 1995, pp. 34-54.
5 Statistical Abstract of the United States: 1994 ( U.S. Bureau of the
Census, 1994), table no. 165. “Health Insurance Coverage Status, by Selected
Characteristics: 1987-92,” p. 118.
6 Cunningham and Monheit, pp. 77-78.
7 Cunningham and Monheit, p. 80. Based on data from the 1977 National
Medical Care Expenditure Survey, 1977 and the National Medical Expendi
ture Survey, 1987. (See exhibit 2, p. 81.)
8 Gloria J. Bazzoli, “Health Care for the Indigent: Overview of Critical
Issues,” Health Services Research, August 1986, pp. 353-93.
9 Ibid., p. 356.
10 Ibid., p. 357.
11 Richard D. Miller, “Another Look at the Medically Uninsured Using the
1987 Consumer Expenditure Survey,” Bureau of Labor Statistics Working
Paper 205, October 1990.
12 A consumer unit is a single person living alone or sharing a household
with others who are all financially independent; members of a household re
lated by blood, marriage, adoption, or other legal arrangement; or two or more
persons living together who share responsibility for at least two out of three
major types o f expenses: food, housing, and other expenses.
13 Elizabeth M. Reise, “A Look at Private Health Insurance Coverage of
Families with Children under 18 Using Data from the Consumer Expenditure
Interview Survey 1989-91,” Proceedings of the Social Statistics Section
(Alexandria, v a , American Statistical Association, 1993), pp. 827-32.
14This includes all children living at home. Presumably, most children who
22 Monthly Labor Review August 1995
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are over 18 and living away from home are independent, and responsible for
their own health insurance. The Consumer Expenditure Survey considers col
lege students who live at school to be separate consumer units.
15The numbers of famiL _:s excluded from the sample are as follows: medic
aid only: 454; medicare only: 32; medicaid and medicare: 16.
16 The total expenditure definition used in the Consumer Expenditure Sur
vey excludes mortgage principal payments (though it includes mortgage inter
est payments), and includes the full purchase price of a vehicle, if one is pur
chased. In the present study total expenditure outlays are defined to include
mortgage principal payments, because they are an important component o f the
homeowner’s budget, and are not easily changed once negotiated. Addition
ally, the full purchase price o f a vehicle is replaced by actual outlays. That is,
if the respondent reports vehicle payments, including finance charges, these are
included rather than the full purchase price, unless the vehicle is purchased
outright.
17Ethnic origin of the reference person is used to define these variables. Fami
lies are defined as black if reference person’s ethnicity is described as “AfroAmerican.” Families are defined as Hispanic if the reference person’s ethnicity
is described as “Mexican American,” “Chicano,” “Mexican,” “Puerto Rican,”
“Cuban,” “Central or South American,” or “Other Spanish.” Families are de
fined as white and other if the reference person’s ethnicity is described as “Ger
man,” “Italian,” “French,” “Polish,” “Russian,” “English,” “Scottish,” “Dutch,”
“Swedish,” “Hungarian,” “Other,” or “Do not know.”
A separate variable identifying race of the reference person (white; black;
American Indian, Aleut, Eskimo; Asian or Pacific Islander; other) is not used
in these definitions. The distinction between race and ethnicity is especially
important for the model results shown later. For example, someone who is
Hispanic by ethnic origin but black by race is still classified as Hispanic in
these models.
18 The number o f uninsured children is calculated by multiplying the aver
age number of children per uninsured family (2.0) by the number of uninsured
families (773). The number o f fully insured children found similarly for the
fully insured families (1.9 multiplied by 2,605). Uninsured children from par
tially insured families are found for “children first” families by multiplying the
percentage of uninsured children (1-0.789) by the number of children in these
families (1.9 multiplied by 347). Similarly, the number of uninsured children
in partially insured, “adult first” families can be calculated. The total number
o f uninsured children (that is, children from uninsured families added to unin
sured children from partially insured families) provides the numerator for a
percent calculation. The total number o f children, regardless of coverage, pro
vides the denominator. If all partially insured families follow the “children
first” strategy, then 11.2 percent of children in the sample are uninsured. If they
all follow the “adult first” strategy, then 15.8 percent of children in the sample
are uninsured.
19 The standard errors o f the means for medical services are 32.49 for the
fully insured and 92.64 for the uninsured.
20 Rose M. Rubin and Kenneth Koelln, “Determinants of Household Out-ofPocket Health Expenditures,” Social Science Quarterly, December 1993 do
721-35.
21 These variables are a subset o f those chosen for the multinomial logit
model described later in the multinomial logit section.
22 See G.S. Maddala, Limited Dependent and Qualitative Variables in
Econometrics (Cambridge, England, Cambridge University Press, 1983), pp.
23 Milton Friedman, A Theory of the Consumption Function (Princeton, NJ,
Princeton University Press for National Bureau of Economic Research 1957)
p. 221.
The use o f total expenditures as a proxy for permanent income is common in
the literature (for example Miller, Reise, and Paulin and Weber). Rubin and
Koelln use an instrumental variable form of total expenditures as a proxy for
permanent income to avoid simultaneous equations bias in predicting health
care expenditures (pp. 727-28). That is, health care expenditures are a sub
component of total expenditures, so using total expenditures to predict health
care expenditures may result in a bias. No such instrument is necessary in
the present case, because only probabilities, not levels, o f expenditures are
predicted.
Other recent studies that use total expenditures as a proxy for permanent
income to model expenditures other than health care include Julie Nelson, “In
dividual Consumption Within the Household: A Study of Expenditure on Cloth
ing,” Journal of Consumer Affairs, Summer 1989, pp. 21-43; and E. Raphael
Branch, “Short Run Income Elasticity o f Demand for Residential Electricity
Using Consumer Expenditure Survey Data,” The Energy Journal, 1993 on
27 Further evidence of the plausibility of this assumption comes from Reise,
“A Look at Private Health Insurance” and Miller, “Another Look.” Both au
thors test for a lack of health insurance coverage. Reise uses the natural log o f
total expenditures in her model, and finds the coefficient negative and statisti
cally significant, indicating that the probability o f a lack o f coverage decreases
with income at a decreasing rate. Miller uses total expenditures and total ex
penditures squared in his model. He finds a negative coefficient for total expen
ditures and a positive coefficient for total expenditures squared. Both coeffi
cients are statistically significant. As in Reise’s study, the signs o f Miller’s
coefficients also indicate the lack of insurance coverage is decreasing at a de
creasing rate with respect to income. If the problem is reversed, that is, the
probability of full insurance coverage is estimated instead of a lack o f cover
age, the signs of the coefficients reverse, indicating that the probability o f hav
ing full insurance coverage increases with income, though still at a decreasing
rate, as postulated in this article.
Note also that both Reise’s and Miller’s specifications are forms o f the BoxCox transformation. Reise, in effect, assumes the optimal value o f 1is zero; that
is, the natural log is the appropriate transformation. Miller assumes the opti
mal value o f 1 is 2; that is, a squared term is appropriate. As noted earlier, in
this study, the optimal value of 1 is found to be 1/8, which is between the Reise
and Miller estimates.
28 Regions are designated by standard U.S. Bureau o f the Census defini
tions.
-9 In Miller, “Another Look,” the author includes a dummy variable for
renters (as opposed to homeowners) “as a proxy for wealth” (p. 8), and finds
that renters are significantly more likely to lack full insurance coverage than
are homeowners (p. 24). In this study a dummy variable is also included to
distinguish families that own their homes outright from families that still pay a
mortgage. Paulin finds that families that own outright spend about 11 cents out
of every additional dollar on health and personal care, compared to 5 cents for
mortgage payers and renters. This may reflect a wealth effect, or simply the
fact that families that own outright have more money available to spend than
those who must pay a mortgage, ceteris paribus. See Geoffrey D. Paulin, “A
Comparison o f Consumer Expenditures by Housing Tenure,” Journal of Con
sumer Affairs, Summer 1995, pp. 164-98, especially p. 189.
the Royal Statistical Society, Series B, 1964, pp. 211-43.
30 The median is chosen, as opposed to the mean, because outlays are not
normally distributed. Table 3 shows that the mean is substantially higher than
the median for all three insurance groups, which would raise predicted prob
abilities. Because the median represents the “middle” family better than the
mean in this case, median outlays are chosen for the reference group.
25 Stuart Scott and Daniel J. Rope, “Distributions and Transformations for
Family Expenditures,” Proceedings of the Section on Social Statistics (Alex
andria, va , American Statistical Association, 1993), pp. 741-46.
31 In fact, ceteris paribus, only families with no earners are predicted to have
a lower probability of full coverage than those families whose reference person
is self-employed.
26Using a computer program written by Daniel J. Rope, the variable 1 was
tested over the a range o f values from zero to one with increments of 1/16.
32 See William J. Wiatrowski, “Who really has access to employer-provided
health benefits?” Monthly Labor Review, June 1995, pp. 36—44.
111- 21 .
FF'
24 G.E.P. Box and D.R. Cox, “An analysis of Transformations,”Journal of
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M onthly Labor Review August 1995
23
Fatal Injuries
Self-em ployed individuals
fatally injured at work
Individuals working for themselves,
especially on farms and in retailing,
typically face a higher risk
of fatal injury than do their
wage and salary counterparts
“His brow is wet with honest sweat.
He earns whate ’er he can,
And looks the whole world in the face,
For he owes not any man. ”
Martin E. Personick
and
Janice A. Windau
—Henry Wadsworth Longfellow
The Village Blacksmith (1842)
orking for oneself can be rewarding
for individuals, like Longfellow ’s
smithy, who place a high value on con
trolling the nature and pace of their efforts and are
not overly concerned about an unpredictable earn
ings stream. Being self-employed, however, can
carry considerable safety risks and responsibilities,
such as tackling hazardous work activities without
adequate resources for safety training and equip
ment and without the oversight and guidance of
government safety regulations. (See the appendix
for a description of worker safety and health cover
age by Federal and State agencies.) In 1993, the
self-employed as a group made up about 1 in every
5 fatal injuries at work, higher than their one-tenth
share of the American work force, according to the
Census of Fatal Occupational Injuries and the Cur
rent Population Survey (C PS).1 And certain groups
of the self-employed faced an especially high risk
of dying on the job, such as older farmers operat
ing tractors and other vehicles and managers and
proprietors tending stores, bars, restaurants, and
repair shops where many robbery-related homi
cides occur.
This article analyzes new information on the
self-employed who are fatally injured at work,
such as their occupation, age, and other charac
teristics; the industry they worked in; and the cir
cumstances surrounding their death. The BLS
W
Martin E. Personick is
an econom ist a n d
Ja n ice A. W indau is
an epidem iologist in
th e O ffice o f Safety,
Health a n d Working
Conditions, Bureau
o f Labor Statistics.
24
M on th ly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
August 1995
Census of Fatal Occupational Injuries is the
source of these data. It cross-references death
certificates, newspapers, and other reports to
verify that fatal injuries were work related and to
obtain key information on the “who and how” of
each incident. Of the 6,271 fatal work injuries
counted in the 1993 b l s census, 1,191 were iden
tified as self-employed individuals, 4,981 were
wage and salary workers, and 99 others were pri
marily family workers.
The self-employed at a glance
Although some counts of the self-employed date
back to the late 19th century, the 1940 Decennial
Census marks the beginning of truly systematic
efforts to count and profile that worker group. In
1940, there were nearly 10 million self-employed
persons operating unincorporated business enter
prises. Nine-tenths of those self-employed were
men, most of them working in agriculture, for
estry, and fishing.2
In 1993, the unincorporated self-employed
still numbered about 10 million, but their char
acteristics and share of the work force had
changed dramatically since 1940. Back then, the
self-employed were about 20 percent of the civil
ian work force; now they are 9 percent of a much
larger labor pool. Services industries, moreover,
have replaced agriculture as. by far the leading
industry of the self-employed, accounting for
two-fifths of that group’s workers in 1993. And
the share of self-employed women has grown
from one-tenth of all self-employed in 1940 to
one-third in 1993; still, that is somewhat lower
than their 45-percent share of all workers.3
The employment characteristics of today’s self-employed
differ in many respects from those of wage and salary work
ers. The following comparisons of such staffing differences
shed some light on why their fatality profiles also differ and
why the self-employed as a group appear to be at a compara
tively high risk of fatal injury.
The self-employed tend to be older than wage and salary
workers, a pattern evident over many decades.4 This differ
ence is especially noteworthy for workers in the oldest age
group because they face a relatively high risk of fatal injury.5
In 1993, about one-fifth of the self-employed were age 55
and older, double the proportion of wage and salary workers
in this age category. The difference is even more pronounced
within agriculture, where older workers are fully one-third
of all the self-employed, but just one-tenth of all wage and
salary workers.
Most self-employed and wage and salary workers work in
service-producing industries, where, with a few notable ex
ceptions such as transportation industries, the risk of fatal
injury is relatively low for both. Staffing divergences within
three goods-producing industries, however, illustrate why the
self-employed as a group face a relatively higher risk of fatal
injury. For example, agriculture, the industry with the high
est rate of fatal injury for all workers, accounted for 13 per
cent of the self-employed, but just 2 percent of those working
for wages and salaries. Construction, another high risk in
dustry, engaged proportionately more of the self-employed
(about one-sixth) than of all wage and salary workers (onetwentieth). And by contrast, manufacturing, an industry with
a relatively low risk of fatal injury, accounted for a smaller
share (one-twentieth) of the self-employed than its one-fifth
share of all wage and salary workers.
About half of all self-employed and wage and salary work
ers held a white-collar job either within the broad occupa
tional grouping of “managerial and professional specialty”
or the classification, “technical, sales, and administrative
support.” Both broad groupings carry a relatively low risk of
fatal injury. However, within these groupings are two occu
pations—managers of food serving and lodging services and
sales supervisors and proprietors—for which there is an el
evated risk of becoming a homicide victim during a robbery.
Together, those two occupations made up a larger share (oneeighth) of self-employed workers than of wage and salary
workers (one-twentieth). Self-employed workers also in
cluded relatively large shares of farmers and construction
tradesworkers, two other occupations with high rates of fatal
injury. But proportionately more of the wage and salary
workers (one-seventh) than the self-employed (one-twenti
eth) were “operators, fabricators, and laborers,” a compara
tively high risk group that includes, for example, motor ve
hicle operators and construction laborers.
Self-employed workers typically work longer hours than
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do wage and salary workers and are paid less. The following
tabulation shows the disparity between the two groups in av
erage hours worked per week during 1993 for those on full
time schedules:6
Average weekly hours
Industry
S elf em ployed
Agricultural.............
Nonagricultural.......
54
48
Wage and salary
47
43
The disparity is even more striking when one looks at the
percentage of workers who logged more than 48 hours a
week:
P ercent working m ore than 4 8 hours
Industry
S e lf em ployed
Agricultural.............
Nonagricultural.......
60
46
Wage and salary
37
23
Thus, the average self-employed worker is exposed to work
hazards for a longer period of time and also may be more sub
ject to the effects of fatigue while operating a vehicle or hazard
ous machinery.7 Finally, self-employed individuals typically
earn less than their wage and salary counterparts and, thus,
appear to have few extra resources to spend on safety education
and equipment that often are provided by employers at little or
no cost to their wage and salary workers.8
The fatalities
The 1993 Census of Fatal Occupational Injuries counted
1,191 fatalities among self-employed persons who had been
working either on a primary or a secondary job at the time of
their death. Although it was designed to count only “the
unincorporated” as self-employed, the b l s fatality census also
includes in this count some owners of incorporated businesses
and members of partnerships if their corporate status could
not be ascertained through normal data collection efforts.
Thus, the coverage of fatalities among the self-employed in
the b l s census is somewhat broader than the Current Popu
lation Survey’s definition of self-employed workers (unin
corporated, primary job only). Because of these differences,
fatality rates for the self-employed and for wage and salary
workers by various worker characteristics and types of cases
are not included in this article.9
Still, much can be learned about the relative fatality risks
of the self-employed by identifying the leading ways in which
they died, the primary industries and occupations where the
fatal injury occurred, and the age group of the self-employed
fatally injured. Tables 1 through 3 profile these characteris
tics both for the self-employed and for the wage and salary
worker, revealing several important differences in fatality
M onthly Labor Review
August 1995
25
Fatal Injuries
patterns between the two.
Fatal event and exposure. Work-related homicide led all
other fatal event and exposure categories for the self-em
ployed and ranked second to highway incidents for the wage
and salary worker (table 1). Homicide accounted for a slightly
larger share of fatal injuries among the self-employed fatally
injured (22 percent) than among wage and salary workers
(16 percent), suggesting that the risk of violent death at work
is higher for the self-employed than for wage and salary work
Fatal work injuries among self-employed and
wage and salary workers, by event
or exposure, 1993
[In percent]
Selfemployed
Event or exposure1
Wage and
salary
Number....................................
Percent....................................
1,191
100
4,981
100
Transportation incident.........................
Highway........................................
Collision between vehicles,
mobile equipment........................
Noncollision....................................
Jack-knifed, overturned..............
Nonhighway (farm, industrial)..........
Noncollision....................................
Overturned.....................................
Fell from and struck by vehicle,
mobile equipment........................
Aircraft.......................................
Worker struck by vehicle....................
Water vehicle......................................
Railway....................................
34
11
41
22
5
4
3
14
13
9
12
6
4
4
4
2
2
3
3
3
1
1
5
6
2
2
Assault and violent a c t........................
Homicide...........................................
Shooting................................
Stabbing.......................................
Self-inflicted injury............................
29
22
19
1
6
19
16
13
2
3
Contact with object, equipment............
Struck by object................................
Falling object..............................
Caught in or compressed by
equipment or object.........................
Running equipment, machinery.....
Caught in or crushed in
collapsing materials.........................
20
12
7
16
8
5
6
3
4
2
2
2
Fall................................................
From roof.......................................
From ladder, scaffold, staging...........
8
2
2
10
2
2
7
3
10
2
2
2
2
2
4
Exposure to harmful substance
or environment.................................
Contact with electric current.............
Exposure to caustic or
noxious substance.........................
Oxygen deficiency, including
drowning, submersion....................
Fire and explosion................................
1 Based on the 1992
Structures.
bls
6
Occupational Injury and Illness Classification
NOTE: Total for a major event category may include data for subcategories
not shown separately. Percentages may not add to totals because of rounding.
M onthly Labor Review
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Federal Reserve Bank of St. Louis
August 1995
ers.10 The self-employed also were more likely to die at work
of a self-inflicted injury than were wage and salary workers.
Nonhighway fatalities, except rail, air, and water inci
dents, were the second leading way in which the self-em
ployed died at work. Many happened on farms and com
monly involved tractors and other farm vehicles overturning
on their drivers or occupants falling from and being struck
by such vehicles. Some nonhighway incidents occurred off
of farms (for example, on industrial premises) and in other
ways, such as self-employed workers killed solely by falling
from a moving vehicle or piece of mobile equipment or by
colliding with other vehicles or striking stationary objects,
such as trees. The whole category “nonhighway incidents,
except rail, air, and water” accounted for 14 percent of the
self-employed fatalities and 4 percent of all wage and salary
worker deaths reported in the 1993 b l s census.
Highway incidents and persons struck by objects other
than vehicles or mobile equipment were the two other event
and exposure categories to account for at least one-tenth each
of the self-employed fatality total. About half of the highway
fatalities resulted from collisions between vehicles or mobile
equipment; most of the rest were noncollision incidents re
sulting from vehicles jackknifing, overturning, or running
off the highway. Falling objects, such as trees and construc
tion materials, also pose a notable hazard for the self-em
ployed. Unlike the other major categories of fatal events,
highway incidents appear to pose a lower fatality risk for the
self-employed than for wage and salary workers.
Occupation of the fatally injured. Farm operator and man
ager was, by far, the occupation with the largest number of
self-employed fatal injuries reported by the 1993 b l s census.
(See table 2.) That farming category accounted for threetenths of the 1,191 self-employed fatalities, triple its onetenth share of the 10 million unincorporated self-employed
reported in the 1993 CPS. The following tabulation shows the
various types of fatal events and exposures that occurred to
the self-employed in farming and other agricultural occupa
tions such as groundskeepers and gardeners:
Farming fatalities:
N um ber.....................................................................
P ercent......................................................................
Transportation incident...............................................
Nonhighway (for example, tractor rollover).......
Other.............................................................................
Contact with object or equipment............................
413
100
49
34
15
34
Struck by object.................................................
17
Caught in or compressed by equipment orobject
O ther.............................................................................
Exposure to harmful substance or environment....
All other events.............................................................
13
4
7
10
Sales occupations accounted for about one-sixth of all selfemployed fatalities. Most of the fatalities to self-employed
salesworkers were robbery-related homicides involving shop-
keepers and other proprietors of small businesses. Sales su
pervisors and proprietors, in fact, were especially risky occu
pations for the self-employed, accounting for 13 percent of
all fatal work injuries among those who work for themselves,
yet making up about 8 percent of the employment total for
the unincorporated self-employed. By contrast, sales super
visor and proprietor occupations had roughly the same share
(about 2 percent) of both the fatality and employment totals
for wage and salary workers.11
The classification “executive, administrative, and mana
gerial” is the remaining occupational group having at least
one-tenth of the fatality total for the self-employed. Like
sales occupations, many workers in this group were homi
cide victims; but most were not, as the following tabulation
of fatal events for self-employed executives, administrators,
and managers points out:
Fatalities to executives, administrators,
and managers:
Num ber.....................................................
Percent......................................................
Assault and violent a c t ................................
H om icid e.....................................................
Self-inflicted injury...................................
Transportation incident................................
Highway.......................................................
A ircraft........................................................
Other.............................................................
Contact with object or equipment............
F a ll...................................................................
Exposure to harmful substance or
environment................................................
Other.............................................................
Fatal work injuries among self-employed and
wage and salary workers, by occupation, 1993
[In percent]
168
100
Occupation1
SelfWage and
employed
salary
45
35
10
19
9
5
5
14
11
9
2
Other characteristics of the fatally injured. More than ninetenths of both classes of workers who were fatally injured
were men, well above their shares of the Nation’s employ
ment. (See table 3.) Men are fatally injured more often than
women primarily because of differences in the jobs men and
women hold. By race, whites dominate employment and fa
tality counts, but Asians, Pacific Islanders, and races other
than white or black appear to have a higher risk of a fatal
injury on the job than the average self-employed or wage and
salary worker.12 A partial explanation for their higher risk
may be that, compared with blacks and whites, they are em
ployed disproportionately in jobs in which the risk of violent
death is relatively high. Homicide accounted for four-fifths
of fatal on-the-job injuries to the self-employed who were not
black or white and for about half of the wage and salary work
ers of these minority races. By contrast, homicide accounted
for 22 percent of all self-employed workers and 16 percent of
wage and salary workers dying on the job. (See table 1.)
As mentioned earlier, older workers face a higher risk of
fatal injury than do younger workers. This is especially true
for the self-employed, 55 years and older. They made up
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more than two-fifths of all self-employed fatally injured in
1993, well above their one-fourth share of all employment
for the unincorporated self-employed. Those self-employed,
aged 65 years and older faced an even higher fatality risk,
accounting for nearly one-tenth of the employment, but nearly
one-fourth of the fatal injuries of the self-employed. Wage
and salary workers also face higher risks with increasing age.
Agricultural industries accounted for more fatalities
among the self-employed than any of the other major indus
try divisions. (See table 3.) Agriculture includes crop and
livestock production as well as services performed on a con
tract or fee basis, such as crop harvesting, veterinary medi
cine, and landscaping. These agricultural activities are
Number............................................
Percent.............................................
1,191
100
4,981
100
Managerial and professional.......................
Executive, administrative,
and managerial........................................
Manager, food serving and
lodging establishment.......................
Professional specialty..............................
Writer, artist, entertainer, athlete.........
17
10
14
5
3
3
1
1
4
1
17
16
13
2
12
7
Service..........................................................
2
10
Farming, forestry, fishing..............................
Farm operator and manager.....................
Farmworker and supervisor......................
Timber cutting and logging........................
Fisher........................................................
42
29
4
3
3
8
1
3
2
1
Precision production, craft, and repair.........
Mechanic and repairer..............................
Vehicle repairer......................................
Construction trade.....................................
Nonsupervisory worker..........................
Carpenter............................................
Electrician............................................
12
4
2
6
4
1
1
19
Operator, fabricator, laborer.........................
Transportation and material
moving operation....................................
Motor vehicle operator...........................
Truck driver.........................................
Cab driver and chauffeur....................
Material moving equipment operator.....
Handler, helper, laborer.............................
10
37
8
7
4
2
22
17
14
2
1
1
3
11
Military occupation........................................
-
Technical, sales, and administrative
support.......................................................
Sales occupation.......................................
Supervisor, proprietor............................
Technical and administrative support........
2
5
5
3
10
8
2
1
2
1Based on the 1990 Occupational Classification System developed by
the Bureau of the Census.
NOTE: Totals for major occupational categories may include data for
subcategories not shown separately. Percentages may not add to totals
because of rounding. Dash indicates that the category is not applicable.
M onthly Labor Review
A ugust 1995
27
Fatal Injuries
highly risky and account for about one-third of the fatal work
injury total of the self-employed, but only about one-eighth
of their employment total. Wage and salary workers in agri
culture also face fatality risks much higher than their 2-percent share of wage and salary employment would suggest.
Interestingly, workers, 55 years and older are a clear major
ity of the self-employed fatally injured in agricultural indus
tries, but are a small fraction of wage and salary workers
dying in that industry.
Retail trade establishments, such as grocery stores and
restaurants, had contrasting risk patterns by class of worker.
Their share of the self-employed who were fatally injured
(18 percent) was slightly larger than their 15-percent share
of the unincorporated self-employed in 1993. But wage and
salary workers in retail trade faced below-average risks of
fatal injury (11 percent share of the wage and salary fatality
total and 17 percent of wage and salary employees). Part of
the difference may reflect the elevated risk of robbery-related
homicide faced by the self-employed when working alone in
retail businesses during evening hours.
Services industries are relatively safe workplaces both for
the self-employed and for wage and salary workers. Both
groups had about a one-eighth share of total fatalities, which
is well below the shares (ranging from 25 percent for wage
and salary workers to nearly 40 percent for the self-employed)
of their employment totals. For the self-employed, “automo
tive repair, services, and parking” was the services industry
reporting the most fatal injuries in 1993; 44 out of 147 deaths
in all services. For wage and salary workers, business ser
vices, such as armored car and personnel supply firms, led
all other services industries; they reported 172 out of 604
service industry deaths.
Like retail trade, construction industries manifest contrast
ing risk patterns by type of worker. But in the construction
industry, it is the wage and salary worker, rather than the
self-employed individual, who faces relatively high fatality
risks on the job.13 Construction makes up 16 percent of all
wage and salary workers fatally injured, triple its 5-percent
share of the employment total for that worker group. By
contrast, the industry’s share of the self-employed fatally in
jured (11 percent) was slightly lower than its 15-percent em
ployment share, suggesting that the fatality rate is lower for
self-employed construction workers than for the average selfemployed worker.
Relatively low fatality risks for the self-employed in con
struction partly reflect their favorable mix of relatively safe
construction work, such as carpentry and painting.14 Differ
ences in work experience and the amount of actual construc
tion work performed are other factors that might help ex
plain why the self-employed in the construction industry typi
cally face a lower risk of fatal injury than do the wage and
salary worker, even within the same trade.
M onthly Labor Review
Digitized for28
FRASER
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A ugust 1995
Summary findings
Data from the 1993 Census of Fatal Occupational Injuries
and 1993 Current Population Survey show that the self-em
ployed as a group sustain a larger share of all fatal work inju
ries than their share of total employment would suggest.
Compared with wage and salary workers, the self-employed
as a group show relatively high risks of fatal injuries, partly
reflecting their disproportionate employment in hazardous
industries like agriculture and construction and their tendency
to be older workers, who are more prone to a fatal injury. In
construction, the fact that the self-employed appear to be at
less risk than wage and salary workers offsets, in part, the
industry’s contribution to the risk differences between the two
working groups. Many occupational groups of the self-em
ployed also tend to be at relatively high risk, especially farm
ers and shopkeepers.
Fatal work injuries among self-employed and
wage and salary workers, by sex, age, race,
and major industry, 1993
[In percent]
Characteristic
Number.................................................
Percent.................................................
Selfemployed
Wage and
salary
1,191
100
4,981
100
Men.......................................................
Women.................................................
95
5
92
8
Both sexes:
Under 35 years.................................
35 to 44 years...................................
45 to 54 years...................................
55 years and older............................
55-64 years..................................
65 years and older........................
16
22
20
42
19
23
39
26
19
17
12
5
85
6
5
4
80
12
3
5
Agriculture............................................
Under age 5 5 ....................................
55 years and older............................
36
15
21
6
4
1
Nonagricultural (private).......................
Forestry and fishing..........................
Mining................................................
Construction......................................
Manufacturing...................................
Transportation and public utilities.......
Wholesale trade................................
Retail trade........................................
Finance, insurance, and real estate ..
Services............................................
64
4
1
11
5
7
2
18
2
12
81
1
3
16
14
16
5
11
2
12
Government.........................................
—
13
Sex and age
Race
W hite....................................................
Black.....................................................
Asian or Pacific Islander.......................
Other or unspecified.............................
Major industry
NOTE: Percentages may not add to totals because of rounding. Dash
indicates that the category is not applicable.
The Census of Fatal Occupational Injuries contains rich
sets of information about how deadly incidents occur. Such
deadly patterns differed by type of worker. The self-employed
were more likely to become a homicide victim than were wage
and salary workers. The next most common ways in which
the self-employed died at work were tractor rollovers and
other nonhighway events, being struck by trees and other
nonvehicular objects, and highway incidents. The latter
deadly events led all others for wage and salary workers, fol
lowed by homicides, being struck by objects, and falls from
elevations. Clearly, safety and health practitioners who study
these fatalities in greater depth could gain valuable insights
into the safety and health problems of the self-employed and
their wage and salary counterparts.
□
Footnotes
1 For a comprehensive account o f the 1993 b l s Census o f Fatal Occupa
tional Injuries, see Guy Toscano and Janice Windau, “The changing character
o f fatal work injuries,” Monthly Labor Review, October 1994, pp. 17-28.
The 1993 employment data are based on the Current Population Survey
( c p s ), conducted for the Bureau o f Labor Statistics by the Bureau o f the Cen
sus. The c p s estimates about 10 million self-employed operating unincorpo
rated businesses in 1993. In addition, there were about 3 to 4 million incor
porated self-employed that year counted in the c p s as “other wage and salary
workers.” The self-employed as a percent o f the total work force (about 120
million in 1993) increases slightly to almost an eighth if both groups o f selfemployed are combined, still less than their share of all fatal injuries at work.
il ,
2See Joseph D. Phillips, The Self-Employed in the United States (Urbana,
University o f llinois, 1962), p. 28.
3 See Phillips, The Self-Employed, for 1940 data and the Current Popula
tion Survey, 1993 annual averages.
“For an analysis o f age differences between the self-employed and work
ers paid wages and salaries, see Eugene H. Becker, “Self-employed workers:
an update to 1983,” Monthly Labor Review, July 1984, pp. 14-18. Current
data are from the c p s , 1993 annual averages.
5 The fatality rate was 7 per 100,000 workers, aged 55 to 64 and 15 per
100.000 workers, 65 years and older. These compare with a rate of 5 per
100.000 workers, ages 25 to 34. For more information on serious injuries
affecting older workers, see Martin Personick and Janice Windau, “Charac
teristics o f older workers’ injuries,” Fatal Workplace Injuries in 1993: A Col
lection of Data and Analysis, Report 891 (Bureau of Labor Statistics, June
1995), pp. 23-27.
6 The hours at work data are from unpublished tabulations o f Current
Population Survey, 1993 annual averages.
7 See Factors that Affect Fatigue in Heavy Truck Accidents, Safety Study
(Washington, National Transportation Safety Board, January
1995).
n t s b / ss -95/01
8 For a discussion of earnings levels by class of worker, see Theresa J.
Devine, “Characteristics o f self-em ployed women in the United States,”
Monthly Labor Review, March 1994, especially pp. 29-32.
9 Even when the incorporated self-employed and individuals who work
as wage and salary workers in their primary job, but who are self-employed
in their second job, are included in the self-employed’s employment figures,
the fatality share for the self-employed is greater than their employment share.
And the fatality-rate gap would narrow somewhat between the self-employed
and wage and salary workers when the longer hours o f the self-employed are
considered.
10Because the overall fatality rate is higher for the self-employed than for
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wage and salary workers, the risk premium for the self-employed is some
what larger than the overall premium for fatal event and exposure categories
that make up an equal or larger share o f all self-employed fatalities than o f
wage and salary workers. For example, let us assume an overall fatality rate
of 10 per 100,000 self-employed and 5 per 100,000 wage and salary work
ers. Applying the homicide shares to each overall rate, the 22-percent share
for the self-employed results in a homicide rate of 2.2 per 100,000 self-em
ployed; the 16-percent share for wage and salary workers results in a 0.8-rate
per 100,000 workers.
Moreover, the self-employed may also face a relatively higher risk for
certain other events and exposures, like fatal falls, when such events are a
slightly larger share o f the wage and salary fatality total than o f the selfemployed fatality total. Using the same overall fatality rates, the self-em
ployed fatality rate for falls would be about 0.8 per 100,000 workers (8 per
cent of an overall rate of 10 per 100,000 workers), compared with 0.5 for
wage and salary workers (10 percent o f a rate of 5 per 100,000 workers).
11Employment by occupation and class of worker appears in unpublished
tabulations from the Current Population Survey, 1993 annual averages.
12Employment by race and class o f worker appears in unpublished tabu
lations from the Current Population Survey, 1993 annual averages. The tabu
lations show that races other than white or black were 4 percent o f the selfemployed and 2 percent o f the wage and salary employment totals that year.
Shares o f fatal work injuries held by “races other than white or black” were
well above the employment shares for this group in 1993.
13 This pattern also holds for an important subset o f occupations in the
construction industry— construction trades. This subset excludes two risky
jobs in the construction industry— construction helpers and laborers— which
employ far more wage and salary workers than self-employed individuals.
Table 2 shows that construction trades composed 6 percent o f all self-em
ployed fatalities, which compares with 11 percent o f total employment for
the unincorporated self-employed in 1993. By contrast, those trades were 10
percent of the fatality total for wage and salary workers, well above their 3percent share of total employment for those workers.
14Risk differences in construction between the two classes o f workers in
part are explained by differences in staffing patterns among individual con
struction trades. Within the construction trades category, the self-employed
are mostly employed as carpenters or painters, two trades having a relatively
low risk o f fatal injury; those two trades are only a third of all wage and
salary workers in construction trades. Electricians, electrical power install
ers and repairers, and structural metal workers, by contrast three occupations
with relatively high fatality risks, together are about 20 percent o f total wage
and salary worker employment in all construction trades, but only 5 percent
of the self-employed total for all construction trades.
M onthly Labor Review
A ugust 1995
29
Fatal Injuries
APPENDIX:
The Census of Fatal O ccu p tio n al Injuries
Definitions. For a fatality to be considered within the scope of the
program, 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 o f the incident as a re
quirement of his or her job. These criteria are generally broader
than those used by Federal and State agencies administering spe
cific laws and regulations. Fatalities that occur during a person’s
commute to or from work are excluded from the census counts.
Data presented in this article include deaths occurring in 1993
that resulted from traumatic occupational injuries. An injury is
defined as any intentional or unintentional wound or damage to
the body resulting 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 o f events within a single workday or shift. In
cluded are open wounds, intracranial and internal injuries, heat
stroke, hypothermia, asphyxiations, acute poisonings resulting
from a short-term exposure (limited to the worker’s shift), sui
cides and homicides, and work injuries listed as underlying or con
tributory causes of death.
Information on work-related illnesses are excluded from the b l s
census because of the latency period of many occupational illnesses
and the resulting difficulties associated with linking illnesses to
work. Partial information on fatal occupational illnesses, compiled
separately, is available for 1991 through 1993 in b l s Report 891.
M easurem ent techniques and lim itations. Data for the Census of
Fatal Occupational Injuries are compiled from various State and
Federal administrative sources— including death certificates, work
ers’ compensation reports and claims, reports to various regulatory
agencies, and medical examiner reports— as well as news reports.
Multiple sources are used because studies have shown that no single
source captures all job-related fatalities. Source documents are
matched so that each fatality is counted only once. To ensure that a
fatality occurred while the decedent was at work, information is
verified from two or more independent source documents, or from a
source document and a followup questionnaire. Approximately 30
data elements are collected, coded, and tabulated, including infor
mation about the worker, the fatal incident, and the machinery and
equipment involved.
Because some State laws and regulations prohibit enumerators
from contacting the next-of-kin, it was not possible to independently
verify work relationship (whether a fatality is job related) for 277
fatal work injuries in 1993; however, the information on the initiating
source document for these cases was sufficient to determine that
30
M onthly Labor Review
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Federal Reserve Bank of St. Louis
August 1995
the circumstances of the incident was likely to be job related. Data
for these fatalities, which primarily affected the self-employed, are
included in the Census of Fatal Occupational Injuries counts. An
additional 49 fatalities submitted by the States were not included
because the initiating source document had insufficient information
to determine work relationship, which could not be verified by either
an independent source document or a followup questionnaire.
States may identify additional fatal work injuries after data col
lection closeout for a reference year. In addition, other fatalities
excluded from the published count because of insufficient informa
tion to determine work relationship may be subsequently verified
as work related. States, therefore, have up to 1 year to update their
initial published State counts. This procedure ensures that fatality
data are disseminated as quickly as possible and that no legitimate
case is excluded from the counts. As data collection methods im
prove, future fatal work injury counts may become more complete.
F ederal/State agency coverage. The Census of Fatal Occupational
Injuries include data for all fatal work injuries, whether they are
covered by the Occupational Safety and Health Administration
(OSHA) or other Federal or State agencies or are outside the scope of
regulatory coverage. Thus, any comparison between the b l s census
counts and those released by other agencies should take into ac
count the different coverage and definitions being used.
Several Federal and State agencies have jurisdiction over work
place safety and health, o s h a and affiliated agencies in States with
approved safety programs cover the largest portion of America’s
workers. However, injuries and illnesses occurring in several other
industries, such as coal, metal, and nonmetal mining, and transpor
tation on water, rails, or in the air, are excluded from o s h a coverage
because they are covered by other Federal agencies, such as the
Mine Safety and Health Administration, the U.S. Coast Guard, the
Federal Railroad Administration, and the Federal Aviation Admin
istration. Fatalities occurring in industries regulated by Federal
agencies other than o s h a accounted for about 11 percent o f the fatal
work injuries in 1993.
Fatalities occurring among several other groups o f workers gen
erally are not covered by any Federal or State agencies. These
groups include self-employed and unpaid family workers, which
together accounted for about 21 percent of the fatality total; labor
ers on small farms, making up about 5 percent o f that total; and
State and local government employees in States without 0SHA-approved safety programs, about 4 percent. (About half of the States
have approved o s h a safety programs which include State and local
government employees in their coverage.)
Unemployment Indicators
International unem ploym ent
indicators, 1983-93
Sweden has the largest increase
in labor underutilization for 1983-93
when part-time work for economic reasons
is taken into account; Japan’s rate
increases most when discouraged workers are added
Constance
Sorrentino
C o nstan ce Sorrentino is
a n e c o n o m is t in th e
Division o f Foreign La
bo r Statistics, Bureau of
Labor Statistics.
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Federal Reserve Bank of St. Louis
even unemployment indicators, known as
U -l to U -7, for nine major industrial
countries were presented in the March
1993 issue of the Monthly Labor Review.' The
data in the initial analysis covered just the year
1989. The indicators have a large cyclical com
ponent, and international relationships might
change, depending on the phase of the business
cycle in each country. To investigate these rela
tionships further, this article presents data for a
series of years, spanning relatively high and low
unemployment periods from 1983 to 1993.
The sequence of indicators U -l to U-7 illus
trates a range of unemployment measures going
from a very narrow to a very broad view. Under
this framework, U-5 is the official, usually cited
U.S. unemployment rate, referred to as the con
ventional measure here. U -l through U-4 nar
row in on certain types of unemployment that
reflect parts of U-5, while U-6 and U-7 portray
broader concepts of underutilization than U-5,
respectively bringing into consideration persons
working part time for economic reasons and dis
couraged workers.
In general, this article reinforces the findings
of the 1993 one. The principal finding of that
study was that Japan and Sweden, the countries
with the lowest unemployment rates as conven
tionally measured, had by far the largest in
creases when the definition was expanded to in
clude persons working part time for economic
reasons and discouraged workers. This contin
ued to be the case. The current study shows that,
S
in times of recession and recovery alike, the
Japanese unemployment rate consistently tripled
when these additional measures of underutili
zation of labor were incorporated. For Sweden,
the most inclusive indicator more than doubled
until 1992-93, when labor market conditions de
teriorated drastically and the conventional rate
jumped sharply, resulting in some closing of the
differential between the conventional and ex
panded rates.
Sweden’s unemployment rate, which was the
lowest of all countries in the earlier study, has
subsequently risen to unprecedented postwar lev
els due to a severe recession. In 1993, Sweden’s
unemployment rate of 9.3 percent, as conven
tionally defined, surpassed the U.S. rate for the
first time. Understanding the effect of Sweden’s
pioneering programs for retraining and employ
ing the unemployed is important to gaining an
appreciation of that country’s labor market situ
ation. The addition of persons in labor market
programs further increased Sweden’s already
high 1993 conventional unemployment rate to
14 percent. Of course, other countries have per
sons in labor market programs, but their pro
portion of the labor force is small compared with
Sweden’s.
In the earlier study, Sweden maintained the low
est rates for most of the indicators, even when la
bor market program participants were added. In
this new study, Japan replaces Sweden as the coun
try with the best labor market performance across
the entire spectrum of indicators in 1992-93.
M onthly Labor Review
August 1995
31
U nem ploym ent Indicators
Upcoming changes in alternative indicators
From 1976 to 1993, the Bureau of Labor Statistics pub
lished a range of indicators known as U -l to U-7. The
framework embodying these indicators was introduced
in Julius Shiskin, “Employment and unemployment: the
doughnut or the hole?” Monthly Labor Review, February
1976, pp. 3-10. From January 1977 until December 1993,
the seven indicators for the United States were published
each month in the news release, Employment Situation.
The Current Population Survey, which is the source of the
U.S. data used in the current article, was revised as of
January 1994. The survey was redesigned to include new
and revised questions regarding individuals’ employment
and unem ploym ent activities, and the collection
methodology was changed to a totally computerized
environment. (For further information, see “Revisions in
the Current Population Survey Effective January 1994,”
Employment and Earnings (Bureau of Labor Statistics,
February 1994), pp. 17-22.) As a result, publication of the
alternative unemployment indicators for the United States
was suspended. A forthcoming article in the Review will
introduce a new framework of alternative indicators for the
United States. The series of international indicators, U -l
to U-7, ends with the 1993 Figures shown in the current
article. Upon its introduction, the new U.S. framework will
be assessed to see whether international comparisons are
feasible.
Another way of looking at the data is to present them in the
form of three elements of labor underutilization: unemploy
ment, part-time work for economic reasons, and discourage
ment with the labor market. Such a classification shows that
unemployment is the largest of the three in all of the countries
studied except Japan and Sweden. Thus, for these two coun
tries, standard unemployment comparisons miss a great deal
of labor force underutilization. Also, ranking the countries ac
cording to total labor underutilization rates differs from rank
ing them according to unemployment rates. For example, Italy
was in the middle of the range of unemployment rates, but had
the highest rate of total labor underutilization.
Data for Australia, which was not covered in the earlier study,
are included in this article. For Germany, the earlier study re
ferred to the former West Germany. In the present study, data
for West Germany continue to be presented until 1992, when
the coverage changes to unified Germany. The addition of what
was formerly East Germany raised the indicators for Germany
throughout the spectrum. Some small revisions are made to
the previously published data for Sweden and the United King
dom, and significant revisions are made to three of the indica
tors for France and to the U-7 indicator for Japan. (See the
appendix for information about these revisions.)
32
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August 1995
Seven indicators
In recognition of the fact that the official rate of unemploy
ment is not ideally suited to all types of analyses or uses, the
Bureau of Labor Statistics for many years published a series
of alternative measures of unemployment based on definitions
that were either narrower or broader than the conventional
measure. The box on page 33 defines the seven indicators.2
Some of the indicators yield lower unemployment figures
than the conventional standard does, while others result in
higher figures. Under the U -l through U-7 framework, U-5 is
the official, usually cited unemployment rate—the rate from
which all the others are derived by either adding or subtracting
different population groups. The first four, narrow, indicators
(U -l to U-4) focus on certain “more serious” types of unem
ployment—respectively, long-term unemployment, job loss,
adult unemployment, and unemployment of seekers of full
time jobs.
U-6 and U-7 portray broader concepts of unemployment than
does U-5, bringing into consideration two additional elements
of underutilization of labor: persons working part time for eco
nomic reasons and discouraged workers.3 U-6 includes the
number of unemployed persons seeking full-time work, plus
one-half of the number of unemployed persons seeking parttime work and one-half of the number of those involuntarily
on part-time schedules for economic reasons. The reasoning
behind this formulation is that involuntary part-time workers
should be counted as at least partially unemployed; similarly,
unemployed persons seeking only part-time work should be
given just half the weight of unemployed persons seeking full
time jobs, because their employed counterparts work, on aver
age, only about half of a full workweek. This indicator moves
from the activity-based concept of the labor force used in all
the earlier indicators to a “time lost” type of concept.
Discouraged workers, added at U-7, are defined as persons
without work who want a job, but who are not looking for work
because they believe that their search will be unsuccessful.4
Discouraged workers are somewhat more broadly defined in
the data presented for Japan and Italy. In both countries, be
cause of the special nature of their labor markets, there is a
sizable group of persons who want work, are available for work,
and are classified as unemployed,5 even though they did not
seek employment in the 4 weeks preceding the survey. These
persons are awaiting the results of previous applications. The
Bureau adjusts the data for Japan and Italy by removing such
individuals from U-5, but adding them to U-7. This group
does not fit precisely into the framework of rates, falling some
where between U-5 and U-7. No similar adjustment is needed
for the other countries studied, because the numbers involved
are small.6
The conventionally defined unemployment rate, U-5, re
mains the most widely accepted measure of unemployment
in all countries. Although the other indicators—particularly
the expanded ones—are viewed with interest, none of them
has been widely adopted by data users for either domestic or
international analysis.7 There are three basic reasons for
this. First, the U-5 definition is simple and objective, in
volving no value judgments about a person’s relative need
for work or personal characteristics. Second, as will be
shown later, while the alternative measures differ signifi
cantly in level, they reflect very similar trends over time;
that is, they all send out essentially the same “signal” re
garding whether labor market conditions are improving or
deteriorating. Third, for purposes of comparison with other
countries—especially the major U.S. trading partners—us
ers recognize the need for a “common currency”: the rate
based on the International Labor Office standards. U-5 is
the most readily available, well-understood, and comparable
measure.
Nevertheless, it is instructive to assess international differ
ences in terms of the alternative measures, because they point
out differences that are not expressed by the conventional
measure.
Period studied
The year 1983 was chosen as the initial year for the analysis
because it was the first year a new series of European Union
labor force surveys8 was compiled in accordance with
International Labor Office (ILO ) concepts that allowed for
international comparisons. A historically compatible series
of indicators could be calculated for the full period 1983-93
for five countries: the United States, Canada, Australia,
France, and the United Kingdom. However, even for three
of these countries, a few indicators were missing for some
years: U -7 was unavailable for France before 1989, and
U -2 began in 1987 for Australia and in 1984 for the United
Kingdom. Japan’s series was fully available from 1984
onward. Thus, only the United States and Canada had the
full complement of indicators available for all of the years
studied.
For the other countries examined, time series analysis for the
period was further constrained by changes in surveys. Because
of the unavailability of comparable data for earlier years, the
German series begins (partially) in 1984, Italy’s in 1986, and
Sweden’s in 1987. Only three of the indicators could be calcu
lated for Germany in 1984; a more complete series (missing
only U-7) begins in 1985.
In 1992, revisions were made in European Union survey
definitions, causing a historical break more significant for
Italy and the Netherlands than for France, Germany, and the
United Kingdom. Because of this break, as well as a signifi
cant modification in the Dutch national definitions, the data
series for the Netherlands terminates in 1991 in this article.
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Italian data for 1992 and 1993 are shown, but the rates for
earlier years are somewhat understated.
The data are annual averages for the United States,
Canada, Australia, and Sweden. Japan’s data refer to Feb
ruary of each year, and the data for the European Union
countries generally refer to the spring, except that Italian
data for 1992 are for October.
Patterns over time
Table 1 shows the seven indicators for the United States and
the nine foreign countries studied for the years from 1983 to
1993 for which data were available. The figures relate to
both sexes combined; figures were also calculated for men
and women separately, but are not shown in the table.9 Some
averages for men and for women are presented later in the
article.
Chart 1 depicts the trend over time of six indicators (U-4
is excluded because it is virtually the same as U-5) for the
United States, Australia, Japan, France, Italy, and Sweden.
Alternative unemployment indicators
U -l Long-duration unemployment rate: Persons un
employed 13 weeks (see footnote 2 in text) or longer, as a
percent of the civilian labor force.
U-2 Job loser rate: Job losers, as a percent of the
civilian labor force.
U-3 Adult unemployment rate: Unemployed persons
aged 25 and older, as a percent of the civilian labor force
aged 25 and older.
U -4 Full-time unemployment rate: Unemployed seek
ers of full-time jobs, as a percent of the full-time labor
force.
U-5 Conventional unemployment rate: Number of
persons not working, but available for and seeking work,
as a percent of the civilian labor force. Only persons on
layoff and persons waiting to start a new job are not re
quired to seek work in the past 4 weeks, a necessary con
dition for all others classified as unemployed.
U-6 Rate encompassing half of the persons working
part time for economic reasons: Number of seekers of
full-time jobs, plus one-half of all seekers of part-time
jobs, plus one-half of all persons working part time for
economic reasons, as a percent of the civilian labor force,
less one-half of the part-time labor force.
U-7 Rate adding discouraged workers: U -6 plus
discouraged workers in the numerator and denominator.
M onthly Labor Review
August 1995
33
U nem ploym ent Indicators
Table 1.
Alternative unemployment indicators, U-1 to U-7, 10 countries, available years, 1983-93
[In percent]
Country and year
U-1
U-2
U-3
U-4
U-5
U-6
U-7
4.0
2.6
2.2
2.1
1.8
1.5
1.2
1.3
2.0
2.8
2.5
5.6
3.9
3.6
3.4
3.0
2.5
2.4
2.7
3.7
4.2
3.7
7.5
5.8
5.6
5.4
4.8
4.3
4.0
4.4
5.4
6.1
5.6
9.5
7.2
6.8
6.6
5.8
5.2
4.9
5.2
6.5
7.1
6.5
9.6
7.5
7.2
7.0
6.2
5.5
5.3
5.5
6.7
7.4
6.8
12.6
10.1
9.6
9.4
8.5
7.6
7.2
7.6
9.2
10.0
9.3
13.9
11.2
10.6
10.3
9.3
8.4
7.9
8.2
10.0
10.8
10.2
6.1
5.4
5.0
4.3
4.0
3.3
3.1
3.3
4.8
5.7
5.9
7.0
6.4
5.8
5.3
4.8
4.0
3.9
4.4
6.1
6.7
6.5
10.3
9.3
8.8
8.0
7.5
6.7
6.6
7.0
9.0
9.9
9.9
11.9
11.2
10.3
9.4
8.7
7.6
7.4
8.0
10.3
11.1
11.0
11.8
11.2
10.5
9.5
8.8
7.8
7.5
8.1
10.3
11.3
11.2
14.3
13.8
12.9
12.0
11.1
9.8
9.5
10.1
12.9
14.2
14.4
15.7
14.8
13.8
12.7
11.7
10.3
9.9
10.6
13.6
14.9
15.2
6.2
5.7
5.1
4.7
4.8
4.1
3.2
3.5
5.9
7.4
7.4
(’)
(’)
(<)
(’)
2.7
2.3
1.8
2.4
4.1
4.4
3.9
7.0
6.3
5.9
5.7
5.9
5.3
4.6
5.1
7.3
8.4
8.7
10.1
9.0
8.1
7.9
8.0
6.9
5.8
6.7
9.6
10.9
11.0
10.0
9.0
8.3
8.1
8.1
7.2
6.2
6.9
9.6
10.8
10.9
12.2
11.0
10.1
10.1
10.3
9.3
8.3
9.4
12.9
14.7
14.8
13.6
12.3
11.2
11.1
11.4
10.3
9.2
10.4
14.3
16.2
16.3
1.4
1.3
1.4
1.6
1.4
1.1
1.0
.9
.9
1.1
.8
.8
.8
.7
.7
.5
.4
.4
.4
.6
2.3
2.2
2.2
2.3
2.1
1.8
1.7
1.4
1.5
1.8
2.2
2.2
2.2
2.3
2.0
1.8
1.6
• 1.5
1.6
1.8
2.6
2.6
2.6
2.8
2.6
2.2
2.1
1.9
1.9
2.2
3.8
3.7
3.7
3.9
3.3
3.1
2.7
2.5
2.7
3.2
7.6
8.0
8.1
8.6
7.7
7.1
6.4
6.0
6.1
7.0
.9
.7
.6
.6
1.2
2.7
5.1
1.2
.9
.7
.8
1.7
3.5
6.4
1.6
1.4
1.1
1.3
2.3
4.2
6.7
2.2
2.0
1.6
1.9
3.3
6.2
9.9
2.2
1.9
1.6
1.8
3.1
5.6
9.3
4.9
4.1
3.7
4.1
6.0
9.5
14.3
5.5
4.5
4.1
4.6
6.9
10.8
15.8
6.7
8.0
8.9
8.8
9.2
8.6
8.1
3.4
.9
4.1
4.2
4.7
4.4
4.1
5.6
6.5
7.2
7.7
8.4
8.2
8.1
8.3
10.2
10.9
10.8
11.3
10.7
10.0
8.0
9.6
10.3
10.3
10.8
10.3
9.7
9.5
11.5
12.5
13.3
13.5
12.8
12.3
0
(’)
(')
(')
(’)
(’)
12.4
United States
1983 ......................................
1984......................................
1985 ......................................
1986 ......................................
1987......................................
1988 ......................................
1989 ......................................
1990 ......................................
1991 ......................................
1992......................................
1993 ......................................
Canada
1983......................................
1984 ......................................
1985 ......................................
1986 ......................................
1987......................................
1988 ......................................
1989 ......................................
1990 ......................................
1991 ......................................
1992......................................
1993 ......................................
Australia
1983 ......................................
1984......................................
1985 ......................................
1986 ......................................
1987......................................
1988 ......................................
1989 ......................................
1990......................................
1991 ......................................
1992......................................
1993......................................
Japan
1984 ......................................
1985 ......................................
1986 ......................................
1987 ......................................
1988 ......................................
1989.......................................
1990 ......................................
1991 ......................................
1992 ......................................
1993 ......................................
Sweden
1987......................................
1988 ......................................
1989 ......................................
1990......................................
1991 ......................................
1992 ......................................
1993......................................
European Union
France
1983......................................
1984......................................
1985 ......................................
1986 ......................................
1987......................................
1988 ......................................
1989 ......................................
34
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August 1995
Continued—Alternative unemployment indicators,
U -l
to
U -7 . 10
countries, available
v e a r s . 1983-93
[In percent]
C ountry a n d y e a r
U -1
U -2
U -3
U -4
U -5
U -6
U -7
7.6
7.5
7.5
8.5
4.5
4.5
5.9
6.9
7.7
7.7
8.7
9.6
9.7
9.7
10.8
12.1
9.5
9.3
10.4
11.5
11.7
11.3
12.7
14.5
11.8
11.5
12.9
14.7
C ontinued— France
1990
1991
1992
1993
............................
............................
............................
............................
G e rm a n y
West G e rm a n y
1983 ............................
1984 ............................
1985 ............................
1986 ............................
1987............................
1988 ............................
1989 ............................
1990 ............................
1991 ............................
(’)
(’)
(’)
(')
(')
5.8
6.2
6.3
6.7
6.2
5.8
5.0
4.2
O
2.4
2.3
2.5
2.1
1.7
1.3
1.1
6.5
6.2
6.5
5.9
5.3
4.6
4.0
6.7
6.9
6.7
6.9
6.4
5.8
4.9
4.1
(’)
7.2
7.0
7.3
6.7
6.0
5.2
4.5
(’)
(’)
(')
(’)
O
(1)
(’)
(’)
(’)
5.0
6.1
3.6
4.4
6.4
7.8
6.4
7.9
6.4
7.7
7.1
8.8
(’)
(’)
6.8
7.2
7.3
7.3
6.3
6.4
8.0
9.3
.6
.7
.6
.6
.5
.6
1.4
1.9
3.3
3.7
3.9
4.3
3.8
3.9
6.0
6.8
7.4
7.9
8.0
8.0
6.9
7.0
9.5
10.4
7.2
7.6
7.7
7.8
6.6
6.8
9.5
10.4
9.7
10.3
10.1
10.0
8.5
9.0
11.5
12.7
15.9
16.1
16.0
15.8
13.8
15.0
6.2
18.0
( 1)
9.5
11.6
11.9
(’)
(’)
(1)
0
8.8
5.4
5.6
5.5
5.6
5.2
4.6
4.0
3.2
O
O
Unified G e rm a n y
1992............................
1993 ............................
Italy
1986.............................
1987............................
1988 ............................
1989 ............................
1990 ............................
1991 ............................
19922 ..........................
1993 ............................
Netherlands
1983 ............................
1984 ............................
1985 ............................
1986 ............................
1987 ............................
1988 ............................
1989 ............................
1990 ............................
1991 ............................
10.4
O
9.2
( ')
( ’)
7.8
7.5
6.9
5.9
5.3
1.2
1.1
.6
.6
9.0
8.7
9.1
8.9
8.5
6.8
5.2
4.7
5.8
7.4
8.2
3.2
2.8
2.7
2.6
2.1
1.5
1.4
2.6
4.0
4.2
0)
10.2
O
O
10.6
(')
12.1
12.4
n
( 1)
8.0
8.1
7.6
6.9
6.4
7.8
7.5
6.9
5.8
5.5
10.0
9.5
8.8
7.8
7.4
12.5
12.4
11.8
10.5
10.2
13.4
13.3
12.6
11.4
10.9
8.5
8.6
9.5
9.5
9.6
7.8
6.6
6.1
7.3
8.4
8.8
13.0
12.5
12.5
12.6
12.2
9.7
8.0
7.5
9.6
11.5
12.1
11.1
11.0
11.5
11.6
11.1
9.1
7.4
7.0
8.6
9.8
10.3
13.1
13.0
13.3
13.4
13.0
10.6
8.7
8.1
10.3
12.2
13.1
13.9
13.8
14.1
14.3
13.6
11.1
9.1
8.4
10.6
12.8
13.8
( ')
( ’)
O
United Kingdom
1983 ............................
1984 ............................
1985 ............................
1986 ............................
1987 ............................
1988 ............................
1989 ............................
1990 ............................
1991 ............................
1992 ............................
1993 ............................
( ’)
1 Not available.
Break in series for Italy. New survey methods were introduced in 1992 that
raised the adjusted U-5 rate by approximately 1 percentage point.
U-6 , rate encompassing persons working part time for ec:onomic reasons;
UI—7, U-6 plus discouraged workers.
SouRCE: Compi|ed by Bureau of Labor Statistics frQm |abor force su(veys for
NOTE: U-1, long-term unemployment rate; U-2, job loser rate; U-3, adult
| unemployment rate; U-4 , full-time unemployment rate; U-5, conventional rate;
each country. Some adjustments are made for comparability with U.S. concepts.
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
M onthly Labor Review
August 1995
35
U nem ploym ent Indicators
C h art 1.
Alternative unemployment indicators, U-l to U-3 and U-5 to U-7, six countries, 1983-93
Australia
United States
Percent
Percent
France
Japan
Percent
Percent
Italy
36
M onthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
Sweden
Percent
Percent
August 1995
Table 2.
Alternative unemployment indicators, U-l to U-7, 10 countries, average rates for available years, 1983-93
[In percent]
Country
Years
U -l
U-2
U-3
U-4
U-5
U-Ó
U-7
Both sexes
United States
Canada ........
Australia.......
Japan ...........
Sweden .........
European Union:
France..................
Germany3 ............
West Germany....
Unified Germany.
Ita ly ......................
Netherlands.........
United Kingdom
1983-93
1983-93
1983-93
1984-93
1987-93
2.2
4.6
5.3
1.2
1.7
3.5
5.5
1 3.1
.6
2.2
5.4
8.5
6.4
1.9
2.7
6.5
9.7
8.5
1.9
3.9
6.8
9.8
8.6
2.4
3.6
9.2
12.3
11.2
3.3
6.7
10.1
13.0
12.4
7.3
7.5
1983-93
1985-93
1985-91
1992-93
1986-93
1983, 1985,
1987-91
1983-93
8.1
5.0
4.8
5.6
7.3
4.6
2.4
1.9
4.0
.9
7.8
6.1
5.8
7.1
4.5
10.4
5.9
5.6
7.2
8.1
10.0
6.2
6.0
7.1
8.0
12.3
6.6
6.3
8.0
10.2
! 12.7
7.6
7.5
«.9
«2.7
7.9
8.2
7.9
11.0
9.4
9.9
11.7
11.7
12.4
12.3
1983-93
1983-93
1983-93
1984-93
1987-93
2.6
4.8
5.6
1.2
2.0
4.3
6.5
’ 3.9
.7
2.6
5.4
8.1
6.4
1.7
3.0
6.5
9.6
8.3
1.9
4.1
6.9
9.9
8.5
2.1
4.1
8.8
11.3
10.1
2.7
5.5
9.5
11.9
10.6
4.3
6.2
1983-93
1985-93
1985-91
1992-93
1986-93
1983, 1985
1987-91
1983-93
6.4
4.2
4.1
4.4
5.2
4.3
2.2
1.9
3.2
.8
6.2
5.0
4.8
5.7
3.0
8.4
5.2
5.0
5.7
5.8
8.0
5.2
5.1
5.8
5.7
9.2
5.5
5.2
6.3
7.5
2 9.2
(4)
(4)
(4)
10.3
6.3
8.5
5.9
«3.7
6.2
8.9
7.3
11.1
7.7
10.7
8.7
11.7
9.0
12.3
1983-93
1983-93
1983-93
1984-93
1987-93
1.8
4.3
4.8
1.3
1.4
2.6
4.3
1 2.0
.5
1.7
5.3
8.7
6.3
2.4
2.3
6.5
9.8
9.2
2.0
3.5
6.7
9.9
8.8
2.8
3.6
9.7
13.7
13.0
4.3
8.2
10.9
14.7
15.5
10.3
6.1
5.8
7.0
11.2
5.1
2.6
1.9
5.1
.9
9.8
7.7
7.3
9.1
7.2
13.6
7.4
6.8
9.7
13.1
12.4
7.6
7.3
8.8
12.0
16.7
8.6
8.1
10.6
15.7
! 17.4
9.6
6.0
5.9
«1.4
11.0
7.3
9.4
10.7
12.2
8.8
17.9
11.7
19.2
12.4
(4)
(4)
(4)
15.9
M en
United States........
Canada .................
Australia................
Japan ....................
Sweden.................
European Union:
France................... .
Germany 3..............
West Germany....
Unified Germany.
Italy........................
Netherlands...........
United Kingdom
Women
United States...........
Canada ....................
Australia...................
Japan .......................
Sweden ....................
European Union:......
France.......................
Germany3 ................ .
West Germany......
Unified Germany ...
Ita ly ...........................
Netherlands..............
United Kingdom
1983-93
1985-93
1985-91
1992-93
1986-93
1983, 1985,
1987-91
1983-93
11987-93.
21989-93.
3 Former West Germany, 1985-91; unified Germany, 1992-93.
4 Data not available.
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
11.8
9.1
( 4)
(4)
(4)
25.7
51988-91.
«1984-93.
SOURCE: Compiled by Bureau of Labor Statistics from labor force surveys for
each country. Some adjustments are made for comparability with U.S. concepts.
M onthly Labor Review
A ugust 1995
37
U nem ploym ent Indicators
The general pattern of all seven indicators in all of the coun
tries studied, including those not shown, is movement in tan
dem. Another observation is that only in the two North
American countries (Canada’s pattern is similar to the United
States’) and Sweden did U -l through U-7 represent a pro
gression from low to successively higher unemployment
rates.
Although U-4 is not shown in the chart, some mention of
it should be made. In most countries, the unemployment
rate relating to full-time workers (U-4) was noticeably higher
than the adult unemployment rate (U-3). The gap between
these two rates was widest in Italy, where adult unemploy
ment is very low and most unemployment is associated with
young persons. By contrast, in Japan, the youth-adult differ
ential was much narrower than in Italy, and the two rates
tended to be the same. Germany and the Netherlands had
the same pattern as Japan for U-3 and U-4.
In all but the Netherlands and the United Kingdom, U-4
(the rate for full-time workers) virtually coincided with
U-5, the conventional measure. In these two countries,
the unemployment rates associated with seekers of full-time
and of part-tim e jobs were widely different. In the
Netherlands, the rate for seekers of part-time jobs was
almost twice as high as the rate for seekers of full-time jobs.
Consequently, U -4 was substantially below U-5 in that
country. In the United Kingdom, the opposite was true, and the
high rate for seekers of full-time jobs was reflected in U -4 ’s
surpassing U-5.
The upward climb of unemployment in Sweden since 1990
is dramatically portrayed in the chart. Sweden’s series begins
with the year 1987, but earlier years would have shown rates in
the range of the low 1987 levels. Sweden’s U-5 rate averaged
3 percent from 1983 to 1986, equivalent to about 2.6 percent
according to the survey methods and definitions used in 1993.
Averages over time
Table 2 presents the indicators in terms of their averages
over the available years of the 1983-93 period. Table 3
expresses these figures in terms of each indicator’s ratio to
the conventional measure, U-5. This is a convenient means
of comparing the various rates within and among countries.
The averages for the period would generally show the same
comparative results as the figures for any given year;
exceptions are the higher levels of unem ploym ent
experienced in Sweden and unified Germany in 1992-93,
which changed some relationships that existed in prior years.
Tables 2 and 3 show the data for the former West Germany
and unified Germany separately.
In each table, figures are shown for both sexes, for men,
and for women. Data for U-7 are not available for Germany.
For France, data on discouraged workers were available only
38
M onthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
August 1995
for 1989-93, and the average for these years is included in
the table.
Tables 2 and 3 recapture some of the findings already por
trayed in chart 1. The ratios form a progression from low to
successively higher rates only in the United States and
Canada. Sweden’s pattern is similar, except that U -4 is
above U-5. All the European Union countries had much
higher ratios at U -l than at U-2, and Australia was more
like the European countries than the North American coun
tries. Italy was at the extreme: on average, long-duration
unemployment made up more than 90 percent of conven
tionally measured unemployment in Italy, while job losers
accounted for only about 10 percent. West Germany had a
very low job loser rate, but unified Germany’s rate was above
the U.S. average.
Table 3 shows that Sweden had by far the largest propor
tionate increases in unemployment as measured by U-6,
which takes into account the hours lost by persons working
part time for economic reasons. The Swedish U-6 rate was
more than 80 percent higher than the U-5 rate, on average,
whereas the increases for the other countries were much
smaller. Sweden’s ratio of U-6 to U-5 declined as unem
ployment rose in 1992-93. However, even the lower values
of this ratio were higher than the U -6/U-5 ratio in other
countries. Germany had the smallest increase in U-6 over
U-5, and even the higher 1992-93 figures for unified Ger
many were lower than for the other countries. In the United
States, U -6 ranged from 31 percent to 38 percent higher
than U-5 throughout the 1983-93 period. Except for Swe
den, other countries also had ratios that fluctuated over time
within a narrow range.
Japan had by far the largest proportionate increase in
unemployment as measured by U-7. The rate accounting for
both persons holding part-time jobs for economic reasons
and discouraged workers was about triple the conventional
measure in every year of the period. In those years in which
unemployment was lowest in Japan (1991-92), U-7 was
about 320 percent higher than U -5; in the year when
Japanese unemployment was highest (1987), U-7 was 307
percent higher than the conventional rate. Thus, a large
contingent of potential workers who are not in the labor force
overhangs the Japanese labor market at all times.
Japan’s increase in U-6 over U-5 was about the same as
that for the United States, but the addition of discouraged
workers made U-7 increase much more in Japan than in the
United States and other countries. Italy also experienced a
large increase in its U-7 rate.
With some differences in degree, the foregoing relation
ships held for both men and women. (See table 3.) For the
narrower indicators, U -l through U-4, the differences be
tween the rates for men and women in relation to U-5 were
not large for most countries. Women tended to have lower
Table 3.
Alternative unemployment indicators, U-l to U -7 ,10 countries, average ratios of each indicator to U-5 for available
years, 1983-93
[In percent]
Country
Years
U-l
U-2
U-3
U-4
1983-93
1983-93
1983-93
1984-93
1987-93
32
47
62
50
47
51
56
1 36
25
61
79
87
74
79
75
96
99
99
79
108
100
100
100
100
100
135
126
130
138
186
149
133
144
304
208
1983-93
1985-93
1985-91
1992-93
1986-93
1983,1985,
1987-91
1983-93
81
81
80
79
91
46
39
32
56
11
78
98
97
100
56
104
95
93
101
101
100
100
100
100
100
123
106
105
113
128
* 127
(4)
(4)
(4)
199
81
76
5 10
e27
84
83
84
111
100
100
124
118
132
124
1983-93
1983-93
1983-93
1984-93
1987-93
38
48
66
57
49
62
66
1 46
33
63
78
82
75
81
73
94
97
98
90
100
100
100
100
100
100
128
114
119
129
134
138
120
125
205
151
1983-93
1985-93
1985-91
1992-93
1986-93
1983,1985,
1987-91
1983-93
80
81
80
76
91
54
42
37
55
14
78
96
94
98
53
105
100
98
98
102
100
100
100
100
100
115
106
102
109
132
2 115
(4)
O
(4)
181
82
79
M2
6 35
81
83
95
104
100
100
113
109
117
115
1983-93
1983-93
1983-93
1984-93
1987-93
27
43
55
46
39
39
43
1 23
18
47
79
88
72
86
64
97
99
105
71
97
100
100
100
100
100
145
138
148
154
228
163
148
176
421
253
1983-93
1985-93
1985-91
1992-93
1986-93
1983,1985,
1987-91
1983-93
83
80
79
80
93
41
34
26
58
8
79
101
100
103
60
110
97
93
110
109
100
100
100
100
100
135
113
111
120
131
2 140
79
68
57
6 16
90
83
77
122
100
100
147
133
157
141
U-5
U-6
U-7
Both sexes
United States.......................
C anada..................................
Australia..............................
Japan ..................................
Sweden ...............................
European Union:
France.................................
Germany3 ...........................
West Germany................
Unified Germany.............
Italy......................................
Netherlands.........................
United Kingdom..................
Men
United States.......................
Canada................................
Australia..............................
Japan ..................................
Sweden ...............................
European Union:
France.................................
Germany3 ...........................
West Germany................
Unified Germany.............
Italy......................................
Netherlands.........................
United Kingdom..................
Women
United States......................
Canada................................
Australia..............................
Japan ..................................
Sweden...............................
European Union:
France.................................
Germany3 ...........................
West Germany................
Unified Germany.............
Italy.....................................
Netherlands.......................
United Kingdom.................
M 987-93
21989-93.
3 Former West Germany, 1985-91; unified Germany, 1992-93.
4Data not available.
*1988-91.
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
8
(4)
214
*1984-93.
SOURCE: Compiled by Bureau of Labor Statistics from labor force surveys
for each country. Some adjustments are made for comparability with U.S.
concepts.
M onthly Labor Review
August 1995
39
U nem ploym ent Indicators
U -l (long-duration unemployment) rates, compared with
U-5, than did men in those countries that were not mem
bers of the European Union. Within the Union, except for
the United Kingdom, the differences between U -l and U-5
were about the same for men as for women. In all the coun
tries, the job loser rate (U-2) was more favorable for women
than for men, compared with U-5. With few exceptions,
adult unemployment rates (U-3) and full-time unemploy
ment rates (U-4) had similar relationships to U-5 for both
men and women.
Greater sex-related differences showed up in the expanded
rates. In every country studied except Italy, underutilization,
as measured by U-6 and U-7, increased to a considerably
greater extent for women than it did for men, and in Sweden
and Japan in particular, the difference was very large. (See
Table 4.
Rank
table 3.) In Sweden, the U-7 rate increased just 50 percent
for men, but about 2-1/2 times for women, over the U-5
rate. In Japan, U-7 for men was more than double the U-5
rate, but for women it was more than 4 times as great as
U-5. In Italy, the ratios of U -6 to U -5 were virtually the
same for both sexes, but the spread at U-7 was less favor
able for women. These tendencies generally held during re
cession and recovery alike.
Rankings
Table 4 ranks the 10 countries examined in terms of each of
the seven indicators, from lowest (best) to highest (worst), on
average, over the available years of the 1983-93 period. Japan’s
labor market outperformed the others with regard to every
Rankings of 10 countries from lowest to highest average rate, available years, 1983-93
U-2
U -l
U-3
U-4
U-5
U-6
U-7
Both
sexes
1.2
1.7
2.0
4.6
5.0
5.3
7.3
7.5
7.6
8.1
Japan
Italy
Netherlands
Sweden
Germany
United Kingdom
Australia
United States
France
Canada
0.6
.9
.9
2.2
2.4
2.7
3.1
3.5
4.6
5.5
Japan
Sweden
Italy
United States
Germany
Australia
France
Netherlands
United Kingdom
Canada
1.9
2.7
4.5
5.4
6.1
6.4
7.8
7.9
8.2
8.5
Japan
1.9
Sweden
3.9
Germany
5.9
6.5
United States
7.9
Netherlands
8.1
Italy
Australia
8.5
Canada
9.7
10.4
France
United Kingdom 11.0
2.4
Japan
Sweden
3.6
6.2
Germany
United States
6.8
8.0
Italy
8.6
Australia
Netherlands
9.4
9.8
Canada
United Kingdom 9.9
10.0
France
Japan
3.3
Germany
6.6
6.7
Sweden
9.2
United States
10.2
Italy
11.2
Australia
11.7
Netherlands
United Kingdom 11.7
Canada
12.3
12.3
France
Japan
7.3
Sweden
7.5
United States 10.1
United Kingdom 12.3
12.4
Australia
12.4
Netherlands
12.7
France
13.0
Canada
15.9
Italy
Germany
(1)
1.2
2.0
2.6
4.2
4.8
5.2
5.6
6.3
6.4
8.5
Japan
Italy
Netherlands
Germany
Sweden
United Kingdom
Australia
United States
France
Canada
.7
.8
.9
2.2
2.6
3.7
3.9
4.3
4.3
6.5
Japan
Italy
Netherlands
Germany
Sweden
United Kingdom
Australia
United States
France
Canada
.7
.8
.9
2.2
3.0
3.7
3.9
4.3
4.3
6.5
Japan
Sweden
Germany
Italy
United States
Netherlands
Australia
France
Canada
United Kingdom
1.9
4.1
5.2
5.8
6.5
7.3
8.3
8.4
9.6
11.1
Japan
2.1
4.1
Sweden
Germany
5.2
5.7
Italy
United States
6.9
7.7
Netherlands
France
8.0
Australia
8.5
9.9
Canada
United Kingdom 10.7
2.7
Japan
Germany
5.5
Sweden
5.5
7.5
Italy
Netherlands
8.7
United States
8.8
France
9.2
Australia
10.1
Canada
11.3
United Kingdom 11.7
Japan
4.3
Sweden
6.2
Netherlands
9.0
9.2
France
United States
9.5
10.3
Italy
10.6
Australia
Canada
11.9
United Kingdom 12.3
Germany
(’)
Japan
1.3
1.4
Sweden
United States
1.8
Canada
4.3
4.8
Australia
United Kingdom 6.0
Germany
6.1
Netherlands
9.6
France
10.3
11.2
Italy
Japan
Italy
Netherlands
United Kingdom
Sweden
Australia
Germany
United States
Canada
France
.5
.9
.9
1.4
1.7
2.0
2.6
2.6
4.3
5.1
Sweden
2.3
2.4
Japan
5.3
United States
6.3
Australia
7.2
Italy
United Kingdom 7.3
Germany
7.7
8.7
Canada
9.8
France
Netherlands
11.0
Japan
2.0
Sweden
3.5
United States
6.5
Germany
7.4
9.2
Australia
9.4
Netherlands
Canada
9.8
United Kingdom 10.7
Italy
13.1
France
13.6
Japan
2.8
Sweden
3.6
6.7
United States
Germany
7.6
8.8
Australia
United Kingdom 8.8
9.9
Canada
12.0
Italy
12.2
Netherlands
12.4
France
Japan
4.3
Sweden
8.2
Germany
8.6
9.7
United States
United Kingdom 11.7
Australia
13.0
13.7
Canada
15.7
Italy
16.7
France
17.9
Netherlands
Sweden
9.1
United States 10.9
Japan
11.8
United Kingdom 12.4
14.7
Canada
Australia
15.5
17.4
France
19.2
Netherlands
25.7
Italy
Germany
(’)
1 ..... Japan
2 ..... Sweden
3 ..... United States
4 ..... Canada
5 ..... Germany
6 ..... Australia
7 ..... Italy
8 ..... United Kingdom
9 ..... Netherlands
10...... France
Men
1 .....
2......
3 .....
4 .....
5 .....
6 .....
7 .....
8 .....
9 .....
10......
Japan
Sweden
United States
Germany
Canada
Italy
Australia
Netherlands
France
United Kingdom
Women
1 .....
2 .....
3 .....
4 .....
5 .....
6 .....
7 .....
8 .....
9 .....
1 0 .....
1 No data available to rank Germany.
NOTE: See table 2 for available years for each indicator.
SOURCE: Table 2.
40
M onthly Labor Review
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Federal Reserve Bank of St. Louis
August 1995
indicator. Sweden was second to Japan except for U-2 (job
losers), where it was displaced by Italy and the Netherlands,
and U-6, where it was virtually tied with Germany for second
place. Sweden’s rankings are undoubtedly affected by the lack
of data for the years 1983-86, which were years of relatively
low unemployment. If they had been included, Sweden would
most likely have outranked Japan, as it did in each year of the
1987-90 period.10 Also, the table ranks Germany’s averages
for the 1985-93 period, with the 1985-91 data referring to the
former West Germany and 1992 and 1993 referring to unified
Germany. Because of the higher unemployment in the former
East Germany, a ranking for unified Germany based only on
the 1992-93 period would have been less favorable for all of
the indicators except U-6.
The United States ranked from third to fourth best for every
indicator except job losers (U-2). At 3.5 percent, the U.S.
average for this rate was relatively high. Indeed, only
France’s and Canada’s U -2 rates were higher. Job loser
unemployment averaged under 1 percent in Japan, Italy, and
the Netherlands.
All indicators for France, Canada (except U -l), and the
United Kingdom, the countries with the highest conventional
(U-5) rates, were at the high (worst) end of the spectrum.
Canada had the highest job loser and adult unemployment
rates and was virtually tied with France for the highest U-6
rate. France’s long-duration unemployment rate (U -l)
ranked highest, while the United Kingdom had the highest
full-time unemployment rate (U-4). Italy, which had a
midrange U-5 rate, had the highest U-7 rate.
The rankings changed somewhat when the sex of the person
was taken into account. The most striking change was for Japa
nese women, who experienced a relatively high U-7 rate. Rank
ing best in their U-6 rate among women in all the countries
Table 5.
studied, Japanese women fell behind women in both the United
States and Sweden when discouraged workers were added.
Dutch women had the highest (again, worst) U-3 and U-6
rankings and the next-to-highest U-5 and U-7 rankings. Dutch
men fared much better in these categories.
The 1993 study presented an indepth analysis of each of
the seven indicators and the reasons behind the international
differences noted. The next two sections highlight results
relating to two of the narrow indicators—U-2 and U -3—
and the section that follows uses the data developed for U-6
and U-7 to present measures of total labor underutilization.
The final section, on Sweden, takes into account that
country’s participants in labor market programs, through a
broader measure of labor underutilization.
Unemployment by former status
Unemployed persons can be classified into four categories
based on their former employment status: job losers, job
leavers, new entrants into the labor force, and reentrants
into the labor force. Table 5 shows each of these four
groups as a percent of the civilian labor force, averaged
for the available years from 1983 to 1993. U -2 focuses
on job losers.
The foregoing analysis showed that U -2 rates were
relatively low in Japan and Europe (except for France),
compared with North America, throughout the period
studied. This reflects the greater level of job security and
protection for regular workers in Japan and Europe. Italy
was an extreme case, with virtually no job loser un
employment, but a very high proportion of unemploy
ment associated with new entrants into the labor market.
Throughout the 1986-93 period, new entrants in Italy
Unemployment rates by former status, average of available years, 1983-93
[In percent]
Country
Job losers
United States.......................................................................'............
Canada ............................................................................................
Australia............................................................................................
Japan ................................................................................................
Sweden .............................................................................................
Job leavers
New entrants
3.5
5.5
3.1
.6
2.2
0.8
1.7
1.4
.9
.3
0.8
.4
1.5
(1)
.5
1.7
2.3
2.2
(')
.6
4.6
2.4
1.9
4.0
.9
.9
2.7
2.0
1.9
2.0
1.4
.2
1.9
2.6
1.3
.4
.5
.3
5.2
1.7
1.0
2.1
1.5
1.6
1.4
1.7
3.7
3.2
Reentrants
European Union
France...............................................................................................
Germany..........................................................................................
West Germany (1985-91)............................................................
Unified Germany (1992-93).........................................................
Netherlands......................................................................................
United Kingdom................................................................................
’ Not available separately; combined rate for new entrants and reentrants was
0.9 percent.
NOTE: Available years as noted on table 1 for U-2.
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SOURCE: Compiled by Bureau of Labor Statistics from labor force surveys
for each country. Some adjustments are made for comparability with U.S.
concepts.
M onthly Labor Review
August 1995
41
Unem ploym ent Indicators
had unemployment rates in the 5-percent range. This
figure stands out because none of the other countries
studied had an unem ploym ent rate for new entrants
exceeding 2 percent during the period.
Among the European Union countries, only France had
a pattern similar to North America’s, with job losers bear
ing the brunt of unemployment among the four catego
ries listed. The 1993 study postulated that this was be
cause 1989 was a year of high unemployment for France,
and job losses tend to be cyclical. However, even in
France’s years of lower unemployment during the 1980’s,
the higher job loser rates persisted. West Germany had
the more typical European Union pattern in most years,
with job losers having rates similar to or lower than those
of job leavers. Nonetheless, unified Germany experienced
much higher job loser rates compared with the other cat
egories. This resulted in the job loser average for Ger
many moving above the averages of the other groups for
the period. The phenomenon was related to the difficul
ties of transition to a market economy in the former East
Germany.
Youth and adult unem ploym ent
Unemployment among adults (aged 25 and older), as re
flected in U-3, was significantly lower than unemployment
among youth (under age 25) in every country studied except
Germany, where a strong apprenticeship system shields
many youth from unemployment. In all the other countries,
there was a significant youth-adult differential, as shown in
the following tabulation of averages for the available years:
Adult
rate
Youth
rate
Ratio,
youth to
adult
United States......................... ............
Canada.................................... ............
5.4
13.1
2.4
8.5
Australia................................ ............
Japan ....................................... ............
6.4
15.9
15.8
1.9
2.5
2.7
5.6
9.7
2.8
S w ed en ................................... ............
European Union:
France ..................................... ............
Germ any................................ ............
7.8
6.0
22.5
7.1
7.2
2.9
2.0
3.6
Unified Germany................ ............
Italy......................................... ............
Netherlands........................... ............
7.0
1.2
1.2
1.0
4.5
25.9
5.8
7.9
15.3
1.9
United Kingdom................... ............
8.2
15.8
1.9
West Germany.................... ............
5.8
7.1
Because of the low youth-adult unemployment differential
in Germany, that country’s U-3 and U-5 unemployment rates
were virtually identical. The incorporation of the former East
M onthly Labor Review
Digitized for42
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Federal Reserve Bank of St. Louis
August 1995
Germany into unified Germany in 1992 did not alter this fact.
In contrast, U-3 was significantly lower than the conventional
U-5 rate in all the other countries studied. (See table 3.)
Italy’s U-3 measure was particularly low in relation to U-5
because youth unemployment there was about 6 times higher
than adult unemployment. Indeed, most Italian unemployment
occurs among persons under age 25, a phenomenon related to
the job loser-new entrant difference for Italy. New entrants
into the Italian labor market tend to be young persons, and
adults with established jobs tend to be shielded from
unemployment in Italy, although they may be subject to
underemployment in the form of reduced hours. Nevertheless,
the gap between youth and adult unemployment closed
somewhat in 1992 and 1993 as the youth-to-adult ratio fell to
under 5 percent. Some of this decline could have been caused
by the changes instituted in the Italian survey in 1992. (See
appendix.)
Elements of labor underutilization
Going beyond the U -l to U-7 framework, we can use the
data developed in this study to analyze labor underutilization
across countries in its three readily measurable forms: un
employment as conventionally defined (the U-5 indicator);
persons working part time for economic reasons (part of the
U-6 indicator); and discouraged workers (added at the U-7
level). In the reformulation of the data that is set forth in this
section, there is no half-weighting of involuntary part-time
workers and persons seeking part-time jobs, as was done with
U -6 and U-7 earlier. Therefore, the new indicator to be pre
sented represents the number of people underutilized to some
degree, either partially or totally.
Two types of measurement are shown in table 6: (1) a
proportionate distribution of the three types of labor
underutilization and (2) each form of underutilization as a
percent of the civilian labor force. (Note that discouraged
workers are not part of the labor force, but if they were added
to the labor force in these calculations, the results would be
virtually the same.) The data are averages for the available
years from 1983 to 1993.
Table 6 and chart 2 show that unemployment is the largest
of the three elements in all of the countries studied except
Japan and Sweden. By this measure, unemployed persons in
the United States comprised, on average, a little more than
half of all underutilized persons. The unemployed were
around three-fifths of the total in Canada, Australia, and the
Netherlands, and accounted for even higher proportions in
France, Germany, and the United Kingdom. (However, Ger
many does not measure discouraged workers, so that the
German proportions relate to only two of the three elements.)
In Japan, unemployed persons made up only somewhat
more than one-quarter of all persons who were underutilized.
Table 6.
Elements of labor underutilization, 10 countries, averages of available years, 1983-93
Percent distribution
Country
United States..........................
Canada ...................................
Australia..................................
Japan ......................................
Sweden ...................................
Percent of civilian labor force
Unemployed
Part time for
econom ic
reasons
Discouraged
workers
Unemployed
Part time for
econom ic
reasons
Discouraged
workers
54.6
64.0
58.6
27.3
40.8
38.0
30.7
32.6
23.7
50.5
7.4
5.2
8.7
48.9
8.7
6.8
9.8
8.6
2.3
3.6
4.7
4.7
4.8
2.0
4.5
0.9
.8
1.3
4.2
.8
12.4
15.3
14.8
8.6
8.9
70.2
85.7
86.9
83.1
45.3
62.9
77.4
28.7
14.3
13.1
16.9
18.9
32.8
17.9
1.1
(1)
10.1
6.2
5.9
7.1
8.0
9.5
9.8
4.1
1.0
.9
1.4
3.3
5.0
2.3
.2
14.3
(’)
(’)
(’)
17.5
15.2
12.7
Total
labor
underutilization
European Union
France.....................................
Germany.................................
West Germany......................
Unified Germany...................
Italy..........................................
Netherlands............................
United Kingdom......................
V)
’ Not available.
NOTE: See table 7 for available years. Persons seeking part-time jobs and
persons working part time for economic reasons are fully counted in this tabu
lation, in contrast to U-6 and U-7, for which they are only half-weighted.
Discouraged workers were the predominant manifestation
of labor underutilization in Japan, at almost half of the total.
Thus, discouraged workers in Japan comprised about the
same proportion of underutilization as unemployed persons
did in the United States. In Sweden, persons involuntarily
working part time were the main element of underutilization.
Persons working part time for economic reasons and dis
couraged workers together added 5 to 7 percentage points to
the unemployment rate in most countries, on average, for
the 1983-93 period. The United Kingdom had the smallest
addition—about 3 percentage points, while Italy had the larg
est—9.5 percentage points.
Unemployment rates, on average for the period, varied
from 2.3 percent in Japan to 10 percent in France. On the
other hand, the rate of total labor underutilization varied
from 8 percent in Japan and 10 percent in Sweden to 17.5
percent in Italy. France, the country with the highest unem
ployment rate, ranked in the middle of the range on the total
underutilization basis because its discouraged worker rates
were very low. (The discouraged worker rates for France were
averages for 1989-93, the only years for which such rates
were available.) Italy, on the other hand, ranked in the middle
of the range of unemployment rates, but had the highest rate
of total labor underutilization.
The economic part-time rate was highest in the Nether
lands, at 5 percent. With the exception of the Netherlands,
involuntary part-time rates in the European Union countries
were significantly lower than in North America, Australia,
and Sweden. The discouraged worker rates were 4 percent
in Japan and 6 percent in Italy, far higher than in any of the
other countries. As noted earlier, the definition of discour
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n
35.8
4.4
4.7
o
(1)
(’)
6.3
.7
.6
SOURCE: Compiled by Bureau of Labor Statistics from labor force surveys
for each country. Some adjustments are made for comparability with U.S.
concepts.
aged workers is somewhat broader in these countries, in
cluding within its scope persons who are awaiting the re
sults of jobseeking efforts. Discouraged worker rates were 1
percent or less in all the other countries studied.
In Japan, large numbers of women who are temporary or
casual workers withdraw from the labor force when they lose
their jobs, rather than seek work. Such workers generally
bear the brunt of labor market adjustments in Japan. In this
way, Japanese employers have flexibility in their work forces
during economic downturns, enabling regular workers—pre
dominantly men in larger Japanese enterprises—to be virtu
ally assured of employment until they retire, under Japan’s
so called lifetime employment system.11
Italy’s labor market matches people with jobs very slowly.
Hence, there is a large number of persons who want work
and are awaiting the results of previous job applications or
are awaiting the results of competitions for jobs in the public
sector (which can take a year or longer), rather than active
ly seeking work. As noted earlier, they have been added to
the discouraged worker figures for Italy, even though they
may not be in a state of mind we would characterize as
discouragement.
Over time, the three component rates of labor under
utilization tended to move cyclically in the same direc
tion, as would be expected, but cyclical movements in
the rates of unemployment were generally greater than
movements in the rates of those working part time for
economic reasons and in the rates of discouraged work
ers. These trends are illustrated in table 7. There were
some exceptions, however.
In the United States, unemployment declined from 7.4 per-
M onthly Labor Review
August 1995
43
U nem ploym ent Indicators
Chart 2. Elements of labor underutilization, averages of available years, 10 countries, 1983-93
Percent
Percent
United States
Australia
Canada
Sweden
Japan
cent in 1992 to 6.8 percent in 1993, but the involuntary parttime and discouraged worker rates remained the same. Thus,
improvement in the labor market was first seen in the unem
ployment rate, but other forms of labor underutilization re
mained high. In previous years, when the declines in unem
ployment rates were greater, these other forms also moved
downward.
Sweden's sharp upward trend in unemployment in the
early 1990’s was accompanied by significant increases
in both involuntary part-time and discouraged workers.
The unemployment rate in 1993 was more than 4 times
as high as the rate in 1987, while the discouraged worker
rate in 1993 was 2-1/2 times the rate in 1987. The invol
untary part-time rate was about 40 percent higher in 1993
than in 1987.
Unified Germany’s upward movement in unemployment
was accompanied by increases in involuntary part-time work
ers. Prior to 1992, the rate of those working part time for
economic reasons moved narrowly and was generally 1 per
cent or less of the labor force. In 1992-93, for unified Ger
many, the rate rose to more than 1 percent of the labor force.
(No data on discouraged workers were available for Ger
many for the entire period studied.)
44
M onthly Labor Review
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Federal Reserve Bank of St. Louis
August 1995
Germany
France
Italy
Netherlands
United Kingdom
Sw eden’s labor m arket programs
Sweden has been a pioneer in the provision of labor mar
ket programs for retraining and employing the unemployed.12
These programs have been used as an economic instrument
for countercyclical purposes. For many years, the programs
helped keep Swedish unemployment low, even during eco
nomic downturns. However, as Swedish unemployment rose
to unprecedented postwar levels in the early 1990’s, the num
ber of persons participating in the programs increased, but
they could no longer hold down unemployment, as they had
in previous, milder recessions. Even after completing the
programs, participants could not find work, due to a lack of
job creation in Sweden.
A special unemployment rate can be constructed to take
into account Sweden’s labor market programs, which absorb
a substantial number of potentially unemployed persons. In
1993, when the conventionally unemployed in Sweden to
taled 415,000, there were, on average, about 220,000 per
sons in these programs. Without such programs, most of
these individuals would probably have been either unem
ployed or discouraged workers.
Sweden’s U-5 rate of 9.3 percent in 1993 would have risen
Table 7. Elements of labor underutilization in 10 countries, available years, 1983-93
Country and year
Unempployed
Part time for
economic Discouraged
workers
reasons
Total
labor
under
utilization
9.6
7.5
7.2
7.0
6.2
5.5
5.3
5.5
6.7
7.4
6.8
6.8
5.6
5.1
4.8
4.7
4.5
4.3
4.0
4.1
4.8
5.0
5.0
4.7
1.4
1.1
1.0
1.0
.9
.8
.7
.7
.8
.9
.9
.9
16.7
13.7
13.1
12.7
11.6
10.6
9.9
10.3
12.4
13.3
12.7
12.4
1985 .......................
1986 .......................
1987 .......................
1988 .......................
1989 .......................
1990 .......................
1991 .......................
1992.......................
1993 .......................
Average, 1989-932...
11.8
11.2
10.5
9.5
8.8
7.8
7.5
8.1
10.3
11.3
11.2
9.8
4.6
4.9
4.8
4.7
4.4
4.0
3.7
3.9
4.9
5.6
6.2
4.7
1.5
1.2
.9
.8
.7
.5
.5
.5
.8
.8
.9
.8
18.0
17.3
16.1
15.0
13.9
12.2
11.8
12.5
16.017.7
18.3
15.3
1985 .......................
1986 .......................
1987.......................
1988 .......................
1989 .......................
1990.......................
1991 .......................
Average, 1985-91 ..
10.0
9.0
8.3
8.1
8.1
7.2
6.2
6.9
9.6
10.8
10.9
8.6
4.0
3.7
3.5
3.8
4.2
4.0
4.1
4.7
6.1
7.0
7.0
4.8
1.6
1.4
1.2
1.1
1.1
1.1
.9
1.0
1.5
1.7
1.7
1.3
15.6
14.1
12.9
13.0
13.4
12.3
11.2
12.6
17.1
19.5
19.6
14.8
2.6
2.6
2.6
2.8
2.6
2.2
2.1
1.9
1.9
2.2
2.3
2.4
2.4
2.4
2.5
1.9
2.1
1.6
1.4
1.6
2.1
2.0
4.0
4.6
4.7
5.0
4.6
4.1
3.9
3.7
3.6
3.9
4.2
9.1
9.5
9.7
10.3
9.1
8.4
7.5
6.9
7.1
8.2
8.6
2.2
1.9
1.6
1.8
3.1
5.6
9.3
3.6
4.4
3.6
3.4
3.6
4.6
5.6
6.3
4.5
.6
.4
.4
.5
.8
1.3
1.5
.8
7.1
5.9
5.3
5.9
8.5
12.5
17.2
8.9
8.0
9.6
2.4
2.9
0
(’)
(’)
(1)
C an ada
1983 .......................
1984 .......................
1985 .......................
1986 .......................
1987 .......................
1988 .......................
1989 .......................
1990 .......................
1991 .......................
1992 .......................
1993 .......................
Average, 1983-93 ..
Australia
1983 .......................
1984 .......................
1985 .......................
1986 .......................
1987 .......................
1988 .......................
1989 .......................
1990 .......................
1991 .......................
1992 .......................
1993 .......................
Average, 1983-93 ..
Sweden
1987 .......................
1988 .......................
1989 .......................
1990 .......................
1991 .......................
1992 .......................
1993 .......................
Average, 1987-93 ..
European Union:
France
1983 .......................
1984 .......................
1 Not available.
2 Averages calculated only for 1989-93 because of lack of data on discour
aged workers in 1983-88.
3 Break In series for Italy. New survey methods were Introduced that raised
the adjusted U-5 rate by approximately 1 percentage point.
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Part time for
economic Discouraged
workers
reasons
Total
labor
under
utilization
10.3
10.3
10.8
10.3
9.7
9.5
9.3
10.4
11.5
10.1
3.3
4.9
4.4
4.2
4.4
3.8
3.4
3.9
5.0
4.1
6.9
6.7
6.9
6.4
5.8
4.9
4.1
5.9
.9
1.0
1.1
1.0
.9
.7
.7
.9
(1)
n
n
(1)
(')
o
(’)
0
(’)
(1)
(’)
(’)
n
(1)
n
n
1992.......................
1993 .......................
Average, 1992-93 ..
6.4
7.7
7.1
1.2
1.6
1.4
n
n
0
n
n
0
Average, 1985-93 ..
6.2
1.0
n
n
7.2
7.6
7.7
7.8
6.6
6.8
9.5
10.4
8.0
3.5
3.8
3.4
3.3
2.9
3.2
3.1
3.3
3.3
6.9
6.5
6.6
6.4
5.8
6.6
5.1
6.1
6.3
17.6
17.9
17.7
17.5
15.3
16.6
17.8
19.8
17.5
11.9
(’)
10.6
(’)
10.0
9.5
.2
(’)
.4
(1)
.9
.9
.7
7.8
7.4
1.0
(1)
2.8
(1)
5.8
6.2
6.4
5.9
5.9
.6
13.1
(1)
13.7
n
16.7
16.6
15.9
14.5
13.9
9.5
5.0
.7
15.2
11.1
11.0
11.5
11.6
11.1
9.1
7.4
7.0
8.6
9.8
10.3
9.8
1.9
2.2
2.2
2.3
2.4
2.2
1.8
1.6
2.2
2.9
3.3
2.3
.8
.9
.9
.9
.6
.4
.4
.3
.3
.6
.7
.6
13.8
14.1
14.6
14.8
14.1
11.7
9.6
8.9
11.0
13.2
14.3
12.7
n
n
n
n
.2
.2
.1
.1
.2
.2
0
(')
(')
n
14.3
13.5
12.8
14.4
16.7
14.3
Germ any
West Germ any
Unified Germ any
Italy
1986 .......................
1987 .......................
1988 .......................
1989 .......................
1990 .......................
1991 .......................
19923 .....................
1993.......................
Average, 1986-93 ..
Netherlands
Japan
1984 .......................
1985 .......................
1986 .......................
1987 .......................
1988 .......................
1989 .......................
1990 .......................
1991 .......................
1992 .......................
1993 .......................
Average, 1984-93 ..
Unem
ployed
Continued— France
United States
1983 .......................
1984 .......................
1985 .......................
1986 .......................
1987 .......................
1988 .......................
1989 .......................
1990 .......................
1991 .......................
1992 .......................
1993 .......................
Average, 1983-93 ..
Country and year
1983.......................
1984.......................
1985 .......................
1986 .......................
1987 .......................
1988 .......................
1989 .......................
1990 .......................
1991 .......................
Average, 1983,1985,
1987-91 ...............
8.8
.8
United Kingdom
1983.......................
1984 .......................
1985 .......................
1986 .......................
1987.......................
1988 .......................
1989 .......................
1990.......................
1991 .......................
1992 .......................
1993 .......................
Average, 1983-93 ..
Note : Persons seeking part-time jobs and persons working part time for
economic reasons are fully counted In this tabulation, in contrast to U-6 and
U-7, for which they are only half-weighted.
SOURCE: Compiled by Bureau of Labor Statistics from labor force surveys for
each country. Some adjustments are made for comparability with U.S. concepts.
M onthly Labor Review
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45
U nem ploym ent Indicators
to 14 percent if all of the individuals in the labor market pro
grams had been unemployed. Adding these persons to the U-7
rate would have increased it from 15.8 percent to 20.8 percent.
A figure of this magnitude would have ranked Sweden, instead
of Italy, as the country with the highest U-7 rate. This is a
major change from the situation in 1989, when a comparably
derived rate left Sweden virtually tied with Japan for the low-
est U-7 rate among the countries studied. In terms of total
labor underutilization, Sweden’s 1993 rate would have in
creased from 17 percent to 22 percent of the labor force. With
U-7 measured this way, Sweden would have had the highest
labor underutilization of all the countries studied. Of course,
other countries have persons in labor market programs, but in
each, the size of the group is small compared with Sweden’s.
Footnotes
A c k n o w l e d g m e n t : The author thanks Neil Bain of the Statistical Office of
the European Union for providing expert advice and many unpublished tabula
tions from the Union’s labor force surveys. Thanks also go to the following
persons in national statistical offices, for providing special tabulations and ex
pert interpretation o f their data: John E. Bregger, Harvey Hamel, and John F.
Stinson, Jr., o f the U.S. Bureau of Labor Statistics; Richard Phillips of the Aus
tralian Bureau o f Statistics; Doreen Duchesne and Earnest Akyeampong of
Statistics Canada; Takahara Yanai o f the Japanese Statistics Bureau; J. L. Faure
o f the French National Institute of Statistics and Economic Studies; Paolo
Garonna, Director General of the Italian National Institute o f Statistics; Alois
Van Bastelaer o f Statistics Netherlands; Anita Olofsson of Statistics Sweden;
and J.B. Werner and Chris Woolford of the U.K. Department of Employment.
Joyanna Moy and William McMichael of the Division of Foreign Labor Statis
tics assisted in tabulating the data. Sara Elder o f the same Division provided
research assistance while working on a cooperative educational assignment.
1 Constance Sorrentino, “International comparisons o f unemployment indi
cators,” Monthly Labor Review, March 1993, pp. 3-24.
2 U—1 has been redefined slightly for comparative purposes. In the pub
lished figures pertaining to the United States, it represented persons unem
ployed 15 weeks or longer, as a percent of the civilian labor force. However,
most other countries break their categories denoting duration of employment at 3
months (13 weeks), rather than 15 weeks. Because U.S. data are available (in
unpublished form) for durations of a single week, these data were used to modify
the U - l measure for the United States to conform with the definition citing 13
weeks or longer as the breakpoint. This modification makes only a slight differ
ence in the U - l rate for the United States, increasing it by about one-tenth of
1 percentage point.
3 U -7 is not available for Germany throughout the years covered and is not
available for France prior to 1989.
4 This was the U.S. definition prevailing prior to the 1994 revisions to the
Current Population Survey. Beginning in 1994, persons classified as discour
aged must also have looked for a job within the past year and must have been
available for work during the reference week. (A direct question on availabil
ity was added in 1994; previously, the availability of these persons had been
inferred from other responses.)
APPENDIX:
5 Italy has excluded these persons from the unemployed since October 1992.
(See appendix.)
6 For example, Canada’s 1993 survey enumerated only 21,000 persons
“waiting for replies” among those who want work and are available for work,
but who are not classified as unemployed. Their inclusion would add 0.1 per
centage point to the Canadian discouraged worker rate. Data from the Statisti
cal Office of the European Communities ( e u r o s t a t ) also indicate very small
numbers of such persons in the major European Union countries, except for
Italy.
7 The Organization for Economic Cooperation and Development ( o e c d ) fre
quently cites data on persons working part time for economic reasons and on
discouraged workers in analyses published in its Employment Outlook series.
The July 1995 edition of Employment Outlook contains a chapter entitled
“Supplementary Measures o f Labour Market Slack,” which examines in detail
the data on involuntary part-time workers and discouraged workers in o e c d
member countries.
8E u r o s t a t processes and disseminates data forwarded by member countries
from labor force surveys conducted each spring. These surveys have been car
ried out annually in most countries since 1983.
9 Tabulations of the indicators by sex are available upon request from the
author.
10 Sweden’s unemployment rates in 1983-86 averaged about 3 percent,
slightly above the average for Japan (2.7 percent). However, Sweden’s rates
for 1983-86 are probably overstated by about 0.4 percentage point for com
parisons, because they include persons seeking jobs within the past 60 days. In
1987, Sweden’s definition of unemployment was changed to come into accord
with the 4-week job search period used in the United States.
11 A deep recession in Japan beginning in the early 1990’s has resulted in
pressures on the lifetime employment system. Indeed, some employers in hardhit industries have begun to solicit the early retirement of middle-aged whitecollar workers who expected lifetime employment. For a further analysis, see
Haruo Shimada, “Recession and changes in labour practices in Japan,” Inter
national Labour Review, vol. 132, no. 2, 1993, pp. 159-60.
12 For further information see Sorrentino, “International comparisons, ”
p. 17, and the accompanying citations.
Revisions a n d addition of statistics on Australia
This appendix presents information on (1) revisions to the Euro
pean Union surveys; (2) revisions to a component of the statistics
on persons working part time for economic reasons in France and
on discouraged workers in the United Kingdom; (3) revisions
made in the methods applied to the data on Japanese unemploy
ment; (4) revisions to account for a break in the series on Swedish
unemployment; and (5) unemployment statistics for Australia, a
country not included in the 1993 study. That study 1 contained an
appendix 2 explaining the sources, methods, and definitions used.
The information is, in general, applicable to the current study and
will not be repeated in this appendix.
European Union surveys.
The European Union surveys compiled
and published by the Statistical Office o f the European Union
M onthly Labor Review
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FRASER
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August 1995
( euro stat ) are the source of data on the alternative indicators for
France, Germany, Italy, the Netherlands, and the United Kingdom.
The concepts and definitions used in the e uro stat surveys have
been derived from the International Labor Office ( il o ) guidelines
since 1983. With minor exceptions, the United States and other
countries also apply these guidelines.
The integration into the 1992 surveys of a more exact implemen
tation of the il o guidelines implies that the comparability between
the 1983-91 series and the new series from 1992 is slightly im
paired. euro stat states that “the fact that both sets o f definitions
continue to rest upon the ILO guidelines ensures that the differ
ences are minimal.”3
The first of the changes instituted in 1992 has to do with the
definition of the population of working age, which has been modi-
Tied to apply to persons aged 15 years or older (instead of 14 years,
as in the previous survey). The effect of this change is minimal, as
very few 14-year-olds were included in the labor force of the Euro
pean Union countries in 1991.
The definition of employed persons is unchanged. The definition
of unemployed persons contains the following differences:
• Persons seeking to become self-employed are now considered
unemployed only if they satisfy the same criteria of seeking work
and availability for work as persons seeking work as employ
ees. That is, they must be taking specific actions to become
self-employed in the past 4 weeks (such as applying for a busi
ness license or looking for a business location) and be available
to start work in the next 2 weeks. Before 1992, these criteria
were not applied to this small group.
• Persons not at work and hoping to be reengaged by a former
employer (“temporary layoffs”) are, similarly, now considered
unemployed only if they satisfy the usual criteria of seeking
work and availability for work, which were not previously ap
plied. These individuals also are a very small group.
• Persons without employment are considered unemployed only
if they are available for work and have used an active method of
job search within the past 4 weeks. The survey questionnaires
were modified to permit active methods to be distinguished from
passive methods. Persons using only passive forms of job
search—awaiting the results of having applied for a job, wait
ing for a call from a public employment office, awaiting the
results of a competitive recruitment exam for the public sec
tor—are no longer enumerated as unemployed.4 In the absence
of comparative data from both the old and new sets of questions,
it is difficult to estimate the effect of this change, but most
member countries had already complied with the new definition.
All three of the foregoing modifications serve to lower unem
ployment, compared with the prior surveys. Together, then, they
could result in some degree of overstatement in those surveys, com
pared with the 1992-93 surveys, e u r o s t a t believes that the effect
of the changes in 1992 were negligible for France, Germany, and
the United Kingdom, but considerable for the Netherlands and Italy.
e u r o s t a t provided the following tabulation estimating unemploy
ment under the old definition and comparing it with unemploy
ment under the new definition in 1992 for four of the countries
(figures are in thousands):
France
Germany
Italy
United Kingdom
............. .............
............. .............
............. .............
............. .............
Old
New
2,524
2,494
3,141
2,795
2,514
2,467
2,191
2,755
The Bureau of Labor Statistics has made adjustments to the pre1992 data for Italy that mitigate the difference indicated by this tabu
lation. These adjustments were also made to the 1989 data for Italy in
the 1993 article and throughout the time series for Italy for 1986-91
in the current article. (See the discussion of Italy in the next column.)
No adjustments were made for the other countries because, except
for the Netherlands, the differences were small, ( e u r o s t a t could not
provide data on the old basis for the Netherlands.)
The changes that were implemented may have resulted in
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Federal Reserve Bank of St. Louis
certain inconsistencies in the data, which should be remedied
as the new version of the survey becomes more familiar. In
some countries, it was not possible for all of the modifications
to be implemented fully. In France, the new questionnaire was
implemented only for that section of the sample which was
interviewed using computers, with the result that nonresponse
rates were very high for some variables. This effect will gradu
ally disappear with the general phasing-in of computer inter
viewing. Nonresponses were distributed by b l s according to
the proportions derived from the respondents.
In the Netherlands, beginning in 1992, the i l o guidelines
were not observed with respect to the 1-hour criterion for clas
sification as employed, so certain figures had to be imputed by
EUROSTAT. The Dutch national definition was changed in 1992 to
include an employment threshold of 12 hours: persons were
counted as employed only if they worked 12 or more hours dur
ing the reference week and as unemployed only if they sought
at least 12 hours of work for that week. The i l o definition rec
ommends the use of a 1-hour threshold for employment and
imposes no hours threshold for the seeking of employment. Be
cause there are no Dutch data relating to these two conditions,
the i l o (and e u r o s t a t ) definition could not be well reproduced
in the data for the Netherlands. Indeed, after careful study, b l s
found the 1992 and 1993 Dutch data out of line with past trends
and decided to exclude those years from the study, ending the
Dutch series of indicators in 1991.
Italy’s statistical office made a major revision to the labor force
survey in October 1992 that brought it more in line with the EUROSTAT
guidelines. A new method of automatic editing and imputation of
missing data was introduced. 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. Under the definitions prevailing prior to 1992, the Italian
national data, as well as the data reported by e u r o s t a t , counted many
persons as unemployed who engaged in passive job searches only,
such as awaiting the results of recruitment exams in the public sector.
In the 1993 study, b l s made an adjustment to exclude these persons,
but data on both the old and the new basis for 1992 indicate that the
adjustment was probably too high. The adjustment of the old 1992
data resulted in an unemployment rate that was 1 percentage point
below the rate for the data on the new basis. This overadjustment
was partially due to inaccurate adjustments for nonrespondents. The
change in the Italian survey methods and questionnaire also had an
impact on the results. The new survey questionnaire, for example,
has produced an increase in reported job search activity by
unemployed persons.
b l s has adjusted Italy’s unemployment rates for 1987-91 down
ward by excluding from the unemployed persons who had not ac
tively sought work in the past 30 days (plus an estimated number of
nonrespondents), according to data reported by the Italian statistical
office. Although this adjustment is probably too high (based on the
aforementioned 1992 relationships), it continues to be used in the
present study because the Italian statistical office has not published
detailed data on the new basis for any period prior to October 1992.
Thus, Italy’s unemployment rates for 1991 and earlier years shown in
this study are likely to be somewhat understated in comparison with
the 1992-93 data.
e u r o s t a t used the October 1992 survey results for Italy, rather
than the spring survey results, because of the aforementioned
change. For all other European Union countries, the 1992 survey
data refer to the spring. Data for 1993 refer to the spring for all
European Union countries, including Italy.
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47
U nem ploym ent Indicators
For France, in the 1993 study, a proxy had
to be used for “persons working part time because they could not
find full-time work,” a component of persons working part time for
economic reasons (involving calculations of U-4, U-6, and U-7).
The proxy was the number of persons working part time who
worked their usual (or more) hours and who were seeking another
or a second job. The 1993 article had noted that “this proxy under
states the true number to the extent that persons working part time
involuntarily did not seek more work.”5 In 1992, an actual figure
for the group working part time because they could not find a full
time position became available from the French labor force survey,
as reported to Eu r o s t a t . The new data revealed that the proxy se
verely understated the size of this group: instead of the 276,000
persons indicated by the proxy, 852,000 persons were enumerated
as working part time because they could not find a full-time posi
tion. Using the actual figure, BLS raised U-6 from 11.6 percent to
12.7 percent in 1992 and moved U-7 up from 11.7 percent to 12.9
percent. U-4, the unemployment rate applicable to persons seek
ing full-time jobs, was revised downward from 11.2 percent to 10.8
percent because the level of the full-time labor force was increased
by the revision. (The full-time labor force includes all persons work
ing part time for economic reasons.) A similar downward revision
was indicated by the 1993 figures. An adjustment was made for all
years from 1983 to 1991, based on the 1992 proportions.
Revision for France.
The British Department of Em
ployment alerted BLS to an error in the calculation of data on dis
couraged workers reported to EUROSTAT. This error has now been
corrected by the Department, and the revised figures were sup
plied to b l s for all years relevant to the study. The effect of the
revision was small, lowering the 1989 U-7 rate from 9.3 percent to
9.1 percent.
Revision for the United Kingdom.
Consultation with the Japanese Statistics
Bureau and statistics available for the first time in the 1994 survey
resulted in some revisions to the Japanese data. The following three
revisions were made:
Revisions for Japan.
• Previously, the entire National Defense Force was subtracted
from the labor force in the surveys, to arrive at the civilian labor
force. However, members of the National Defense Force who
reside in private households are included in the surveys, and
they amount to about half of the total National Defense Force.
Therefore, only half of the National Defense Force should be
subtracted from the reported labor force.
• A previous adjustment to the Japanese data added all per
sons, except students, waiting to start a new job within 30
days to the unemployed, for comparability with U.S. con
cepts.6 This adjustment was too high, because some of these
persons were not available to begin work, a requirement
under U.S. concepts, and no information was available on
their number. The February 1994 Report on the Special Sur
vey of the Labour Force Survey provided such information
for the first time, indicating that about half of the persons
enumerated as waiting to start a new job in March (exclud
ing students) were not available for work in February.7
Therefore, b l s has excluded half of these persons from the
adjustment in all years of the study period.
• The method of allocating “jobseekers not in the labor force”
according to whether they were seeking full-time or parttime work was modified, on the advice of the Japanese Sta-
48
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August 1995
tistics Bureau. The result was an increase in the number of
persons seeking a full-time job and a decrease in the num
ber of persons seeking a part-time job.
The overall effect of these changes was small, lowering both the
Japanese conventional unemployment rate and the alternative in
dicators by no more than one-tenth of 1 percentage point in some
years and leaving them unchanged in most years.
A more significant change is the b l s revision of the data on dis
couraged workers used in the U-7 rate for Japan. Discouraged
workers are not enumerated as such in the Japanese survey. In the
1993 study, BLS constructed an estimate of discouraged workers
under U.S. concepts by summing the following groups: (1) all per
sons who were not in the labor force, who wanted work but were
not seeking it because there was “no prospect of finding a job,” and
who said that they were available to take a job if they found one;
(2) half of the persons who were not in the labor force, who wanted
work but who were not seeking work because there was “no pros
pect of finding a job,” and who were either not available or unde
cided about their availability for work if offered a job; and (3) half
of the persons enumerated as unemployed, but who were not seek
ing work in the past 4 weeks because they were awaiting the re
sults of previous job applications. The rationale for half-weighting
groups (2) and (3) was that they seemed to only partially fit the
U.S. concept of discouraged workers.
In the current study, b l s has reconsidered the treatment of groups
(2) and (3). This réévaluation led to the elimination of group (2)
and the inclusion of all persons in group (3), rather than only half
of them, in the estimate of discouraged workers for Japan. Overall,
the revised method resulted in a decrease of about 0.7 percentage
point in Japan’s U-7 rate: the rate published for 1990 in the 1993
article was 7.2 percent, and it decreased slightly to 7.1 percent due
to the preceding three revisions. The rate decreased further to 6.4
percent with the changes in the method of determining the number
of discouraged workers.
Some discussion of the U.S. method of enumerating discouraged
workers prior to 1994 is necessary to explain the reasons behind
the elimination of group (2). All persons not in the labor force are
first asked, “Do you want a regular job now, either full or part
time?” All who respond “Yes” or “Maybe, it depends” are then
asked why they did not look for work in the previous 4 weeks. If
multiple responses are given, reasons indicating that respondents
are not discouraged take precedence over reasons indicating that
they are. For example, if the multiple responses are “believes no
work is available” and “in school,” the respondent is not classified
as discouraged. Thus, an implied availability test is built into the
classification method.
In the Japanese survey, persons not in the labor force are first
asked whether they want work. The question is phrased as follows:
“Do you wish to do any work for pay or profit?” Those responding
“Yes” or “Yes, if conditions are favorable” are then asked why they
are not looking for work. Unlike the U.S. survey, which allowed
multiple responses, the Japanese survey permits only one response.
Presumably, the response given is the main reason why the person
is not seeking work. Thus, all respondents who indicate that they
are discouraged (“no prospect of finding a job”) are potentially
discouraged under U.S. concepts.
The Japanese survey then asks an explicit question about the
respondent’s availability: “If you find a job now, can you take it
up?” Possible responses to this question are “Yes, immediately,”
“Yes, but later,” and “No or undecided.” The main point to note is
that the U.S. survey had an implied availability requirement, while
the Japanese survey actually asks explicitly whether a person could
take up a job now if he or she found one.
The U.S. and Japanese questions are clearly different, and a decision
must be made on the best match with the U.S. concept, b l s decided
that the responses “Yes” and “Yes, if conditions are favorable” to the
first question in the Japanese survey approximate the responses “Yes”
and “Maybe, it depends” to the first question in the U.S. survey. Of
those who answer in either of the two ways mentioned in the Japanese
survey, all who further respond “no prospect of finding a job” and
also respond “Yes, immediately” or “Yes, but later” are taken to be
discouraged workers under U.S. concepts. The group responding
“Yes, but later” is included because these are persons who would
accept a job now to start later. It is likely that a person in this situation
would have been enumerated as discouraged in the U.S. survey.
However, those responding “no or not decided” to the last question in
the Japanese survey w’ould probably not have been counted as
discouraged in the United States, as those who meant “no” would not
be counted because they were not available. Those who were not
sure of their availability (“not decided”) would most likely not be
classified as discouraged under the U.S. concept either, because they
were undecided about their availability rather than about their desire
for a job. They are apparently interested in having a job at some time,
but are not sure they would accept a job now even if one were offered.
This implies a stage of labor force inactivity that lies beyond the
scope of being a discouraged worker under U.S. concepts.
Consider now the group of persons who are classified as unem
ployed in the Japanese survey, but were not considered unemployed
under U.S. concepts because they were not actively seeking work
in the past 4 weeks. Instead, they were awaiting the results of pre
vious job applications, b l s subtracts this group from U-5. Mem
bers of the group are in a situation somewhere between unemploy
ment and discouragement. Some may be discouraged, while others
are waiting for developments in the process of job selection, but
are ready and willing to go to work now. These latter individuals,
as well as those who were truly discouraged, should be fully, rather
than partially, counted in a measure of underutilization, and it was
decided to count them fully in the U-7 measure.
In 1993, the
measurement period for the Swedish labor force survey was
changed to represent all 52 weeks of the year, rather than 1 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. One reason for the increase
is that the prior surveys for the month of June were taken in a
week before students were out of school; now all weeks in June
are surveyed, and school leavers seeking vacation work are
included in the unemployed. Other school vacation or holiday
periods are also more completely covered by the new survey. As
a result, youth unemployment moved upward more sharply in 1993
than would have been the case under the previous surveys.
Statistics Sweden has published adjustment factors for 1987-92
in considerable detail, and b l s has applied these factors to arrive
at adjusted figures for these years.
Data needed to adjust the Swedish data on discouraged workers
to U.S. concepts are not published. Statistics Sweden has provided
unpublished data to BLS for the years 1989 and 1991-93. Figures
for the other years were estimated on the basis of proportions emerg
ing from these data.
In Sweden, the concept that corresponds to “discouraged worker”
is latent arbetssokande, or “potentially looking for a job.” Falling
into this category are persons who wanted work and were available
for work in the reference week, but who were not seeking work for
Break in series and adjustments fo r Sweden.
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reasons related to the labor market (for example, because no suitable
work was available locally or because they thought they had little
chance of finding work). One of the reasons listed in the Swedish
survey is “never got around to looking for work.” In addition, under
Swedish definitions, full-time students who were currently available
and actively seeking work during the school term are included in the
concept of latent arbetssokande. Both of these groups have been
excluded from the discouraged worker count for comparability with
U.S. concepts. The students (published data on their numbers are
available each year) have been reclassified as unemployed under the
definition of U-5, while people who “never got around to looking for
work” (number provided by Statistics Sweden for 1989 and 1991-93
and estimated by b l s for other years) remain outside the labor force.
The adjustment for students is normally small, but in 1993 it be
came more significant because of both the general rise in Swedish
unemployment and the changes in the Swedish survey’s timing. In
1993, the adjustment resulted in an increase in the Swedish U-5 rate
from 8.1 percent to 9.3 percent. Before 1992, the number of students
looking and available for work during the school term was very small
each year.
In addition to the preceding adjustments for historical compara
bility, several small adjustments were made to the Swedish data on
persons working “part time for economic reasons,” for comparabil
ity with U.S. concepts. For the 1993 study, Statistics Sweden pro
vided b l s with unpublished tabulations of adjusted data for 1989.
Because the adjustments were very small, b l s has applied the 1989
proportions to adjust data for the other years.
Australia. The Australian Bureau of Statistics compiled the data for
the U—1 to U-7 indicators for this article based on specifications
supplied by the Bureau of Labor Statistics. The data are annual aver
ages for the period 1983-93 derived from the monthly labor force
survey. The Australian survey is very close in concepts and defini
tions to the U.S. labor force survey, and no adjustments were made to
any of the indicators for comparability with U.S. concepts.
There is a slight understatement of persons working part time for
economic reasons in the Australian statistics because the category
“bad weather and plant breakdown” could not be divided into two
separate subcategories. Working part time because of “bad
weather” is not considered an economic reason in the U.S. survey,
while doing so because of a “plant breakdown” is an economic
reason. On the advice of the Australian Bureau of Statistics, BLS
decided to exclude the entire category.
Data on discouraged workers in Australia were available not for
every month, but generally only for March and September of each
year. The Australian Bureau of Statistics annualized the semian
nual figures for this study. Data for job losers (U-2) were available
only from 1987 onward, because no such data were collected in the
earlier years.
The appendix to the 1993 study included a tabulation showing,
for each country, the significant aspects of coverage and reliability
of the labor force surveys used to calculate the alternative indica
tors. The following tabulation gives similar data for Australia, re
lating to the year 1989:
•
•
•
•
•
•
•
Number of households in sample: 30,903
Number of persons in sample: 66,769
Sampling ratio: 0.5 percent
Origin of sampling frame: population census
Unemployment rate, 1989: 6.2 percent
One standard error: 6.1 percent to 6.3 percent
Two standard errors: 6.0 percent to 6.4 percent.
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Unem ploym ent Indicators
Footnotes to the appendix
1Constance Sorrentino, “International comparisons o f unemployment indi
cators,” Monthly Labor Review, March 1993, pp. 3-24.
2Ibid., pp. 19-24.
3Labour Force Survey: Results, 1992 (Luxembourg: Office for Official
Publications o f the European Union, 1994), p. 10.
“However, persons only looking at advertisements in newspapers or journals
are counted as unemployed in the 1992 and earlier European Union sur
veys. Such a form o f job search is not enough for classification as unem
ployed in the United States, but it is in Canada, where those who em ploy
only this method account for about 5 percent o f the unemployed. In the
European Union countries, indications are that this group is also in the 5percent range o f the unemployed. No adjustment has been made on this
point for Canada or the European Union countries. (Although for Italy,
because the group is relatively large, an adjustment is made to exclude
passive jobseekers from U -5 and add them to U -7 prior to 1992; for 1992
50
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August 1995
and 1993, data on such persons continue to be collected even though they
are no longer counted as unemployed in the U -5 measure. For those 2
years, b l s has added them to U -7 without needing to subtract them from
U -5 .) In Japan, the number o f passive jobseekers— mainly persons await
ing the results o f having applied for a job — is also large, and an adjust
ment is made to exclude them from U-5 and add them to U -7 .
5 Sorrentino, “International comparisons,” p. 21.
6 In January 1994, the U.S Current Population Survey definitions were
changed to require a job search on the part of persons waiting to start a new job
within 30 days. However, the data used in this article are not adjusted to the
new U.S. concept, but remain in accord with the concepts in place prior to
1994.
1Report on the Special Survey of the Labour Force Survey (Japanese Statis
tics Bureau, Management and Coordination Agency, 1994).
Incom e Inequality
A surge in growing
incom e inequality?
Examination of a reported surge in income inequality
in 1993 indicates that, despite changes
in survey methodology, patterns of employment growth
were consistent with greater income dispersion
Paul Ryscavage
Paul R yscavage is a
senior labor econom ist,
Housing a n d House
hold Econom ic
Statistics Division,
Bureau o f th e Census,
The views expressed in
this article are th e
author's a n d are not
a ttrib u ta b le to the
Bureau o f th e Census.
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Federal Reserve Bank of St. Louis
ast fall, the Census Bureau announced
that in 1993 incomes had dropped and
poverty had increased. The Agency also
reported that income inequality had risen.1 The
latter piece of news received much attention,
similarly to other reports in recent years that
have focused on the growing dispersion in the
distribution of household incomes.
Inequalities of various kinds in the United
States have become a popular topic in the me
dia. But growing income inequality is particu
larly worrisome because of its immediate impli
cations for social conflict and tension. The
economist Paul Krugman recently wrote: ‘The
ultimate effect[s] of growing economic dispari
ties on our social and political health may be
hard to predict, but they are unlikely to be pleas
ant.”2 Krugman’s statement is significant be
cause the size of the 1992-93 increase in income
inequality reported by the Census Bureau could
be easily characterized as a surge. The Gini in
dex, one of the tools the Agency uses to measure
income inequality, rose from .434 in 1992 to .447
in 1993, the largest 1-year increase since the sta
tistical series on household income inequality
began in 1967.3 (See chart 1.) But this apparent
surge was qualified by the Census Bureau in its
analysis of the data.
The Census Bureau cautioned that the size of
the increase may have been an artifact of techni
cal changes made in how the data on income
were collected in the Current Population Survey
(CPS).4 In addition, other changes to the CPS could
have affected the income data for 1993.
The increase in inequality nevertheless oc
curred at a time when an increase might have
L
been anticipated. The recession of 1990-91 had
an unusually strong impact on well-paid whitecollar workers caught in the downsizing of much
of corporate America. In the ensuing recovery
between 1991 and 1993, many of these workers
resumed their full-time careers. Not only was
employment rising and unemployment falling,
but according to the Bureau of Labor Statistics,
when the data are stratified by occupation, most
of the net increase in employment in the 1992—
93 period occurred in jobs paying above-aver
age wages.5 The question therefore becomes,
How much of the increase in income inequality
between 1992 and 1993 was due to changes in
the economy, and how much was due to techni
cal changes in the c p s ?
This article explores both aspects of this ques
tion in a descriptive way, to provide users wi‘h
further evidence concerning the issue of rising
income inequality between 1992 and 1993. First,
CPS income data are discussed—in particular,
changes that were made in the collection of the
1993 data. Then, long-run and short-run trends
in household income inequality are reviewed.
Next, the 1992-93 changes are examined, first
from the standpoint of the technical changes in
the CPS and then from the standpoint of the
changes that took place in the economy. Finally,
the conclusions of the analysis are presented.
cps
d ata and technical changes
The CPS, of course, is one of the primary sources
of income data used by researchers for measur
ing and studying how the Nation’s income (as
well as earnings) distribution has changed. A
M onthly Labor Review
August 1995
51
Income Inequality
survey of some 60,000 households, the CPS is designed to
measure employment and unemployment each month for the
Bureau of Labor Statistics by means of a series of questions
relating to current labor force activity. In March, an addi
tional series of questions, called the Annual Demographic
Supplement, is asked. These questions concern the work ex
perience and the sources and amounts of income of survey
members in the previous calendar year.
Concept and limitations. The CPS questions on income re
late to money income only (that is, they exclude all noncash
income items, such as food stamps and employer-provided
health insurance, as well as any capital gains), before de
ductions for Federal, State, and local taxes are applied.
Money income is broken down into labor market money
income (wage and salary earnings, as well as farm and non
farm self-employment income) and non-labor-market money
income (for example, interest, dividends, and pensions).
The money income data collected in the CPS also contain
certain limitations. Underreporting of income and trunca
tion bias are two limitations that have particular significance
for studying income inequality. Because the CPS is based
on a probability sample of households, all the estimates de
rived from it are subject to sampling and nonsampling er
Chart 1.
rors. The income estimates are known to be biased down
ward due to nonsampling error (relating, for example, to
noninterviews, undercoverage, inaccurate responses, and
missing data). For 1990, the CPS collected data on 8 8 per
cent of aggregate income derived from independent esti
mates. While it did quite well for wages and salaries (ac
counting for 97 percent of such income), it did poorly for
dividend income (gamering information on only 33 percent
of this source of income).6 Obviously, underreporting of in
come can affect income inequality measurements, because
both the receipt and the amounts of certain income items
vary across the distribution.
Truncation bias occurs as a result of the suppression of
income amounts above a certain upper limit. These amounts
are suppressed in order to reduce the effects of interviewer
error and to provide confidentiality to survey respondents.
However, the limits, or top codes, can be problematic in the
measurement of income inequality:7 if the distribution is be
coming more unequal as a result of rising incomes at the
upper end, top codes will bias measurements of income in
equality downward, because the high incomes will be sup
pressed. Constant nominal-dollar top codes have been used
in the CPS questionnaire and are increased from time to time
to accommodate rising incomes. While one-time adjustments
Gini index, household income distribution, 1967-93
Index
Index
52
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Federal Reserve Bank of St. Louis
0.45
0.44
0.43
0.42
0.41
0.4
0.39
0.38
August
1995
reduce truncation bias, the top codes will eventually become
problematic again.
Technical changes. During the 1980’s and early 1990’s, the
Bureau of Labor Statistics, with the assistance of the Census
Bureau, was engaged in an effort to modernize the monthly
CPS. In general, the focus of the modernization was on rede
signing the monthly labor force questionnaire and introduc
ing a system known as computer-assisted survey information
collection (CASIC). Beginning in January of 1994, the new
CPS was put into operation. The redesign had implications
for the Annual Demographic Supplement conducted in
March of that year. While the questions on work experience
and income concerning calendar year 1993 were not changed
from those of previous years, the new CASIC system was used.
The CASIC technology replaced the traditional paper-andpencil interviewing procedure. In that procedure, two sepa
rate questionnaires—the Monthly Labor Force questionnaire
and the Annual Demographic Supplement questionnaire—
were filled out by the CPS enumerator in the course of the
March interview. In the CASIC system, all the CPS questions
are administered from a computer (either a laptop or a com
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puter located in a centralized telephoning facility), as if only
one questionnaire is in use. Unlike previous March CPS in
terviews, in which the interviewer had to physically shift
from the labor force questionnaire to that on work experi
ence and income, the mechanics of CASIC avoid any signifi
cant interruption of the interview process.
In addition to this change in mode of interview, two other
technical changes occurred in the March 1994 c p s that could
affect income data and the measurement of income inequal
ity for 1993.8First, as occurs after every decennial census of
the population, data from Census Bureau surveys are
reweighted in accordance with estimates of the civilian
noninstitutional population derived from the most recent de
cennial census. The CPS income data for 1993 reflect new
weights derived from the 1990 census, and they have also
been adjusted for the estimated census undercount.
The second change concerns top codes. As mentioned
earlier, top codes used in the CPS are occasionally increased
to reflect rising nominal incomes; such an increase occurred
in the March 1994 CPS. The most important top code that
was increased related to earnings from the longest job or
business. It was increased from $299,999 to $999,999 be-
Monthly Labor Review
August
1995
63
Income Inequality
$50,000 (31.0 percent, compared with
39.3 percent), and slightly fewer below
[In percent]
$15,000 (23.4 percent, compared with
25.1 percent). Median household income
Lowest
Second
Third
Fourth
Highest
Top
Gini
IfeCf
grew from $28,434 in 1967 to $33,685
fifth
fifth
fifth
fifth
fifth
5 percent
index
by 1989, but then declined to $31,241 in
1993, largely reflecting the recession of
1967...........
4.0
10.8
17.3
24.2
43.8
17.5
0.399
1968...........
4.2
11.1
17.5
24.4
42.8
16.6
.388
the early 1990’s. Had the rate of growth
4.1
1969...........
10.9
17.5
24.5
43.0
16.6
.391
in median household income occurred
uniformly across the entire distribution
1970...........
4.1
10.8
17.4
24.5
43.3
16.6
.394
19711..........
4.1
10.6
17.3
24.5
43.5
16.7
.396
from 1967 to 1993, there would have
1972...........
4.1
10.5
17.1
24.5
43.9
17.0
.401
been
no change in inequality.
1973...........
4.2
10.5
17.1
24.6
43.6
16.6
.397
In measuring inequality, the Census
1974...........
4.3
10.6
17.0
24.6
43.5
16.5
.395
1975...........
4.3
10.4
17.0
24.7
43.6
16.6
.397
Bureau ranks household incomes from
1976...........
4.3
10.3
17.0
24.7
43.7
16.6
.398
poorest
to richest and then divides them
1977...........
4.2
10.2
16.9
24.7
44.0
16.8
.402
into
equal
quantiles. From such a rear
1978...........
4.2
10.2
16.9
24.7
44.1
16.8
.402
19792..........
4.1
10.2
16.8
24.7
44.2
16.9
.404
rangement, it becomes possible to ob
serve how much of aggregate income is
1980...........
4.2
10.2
16.8
24.8
44.1
16.5
.403
received
by similar proportions of house
1981 ...........
4.1
10.1
16.7
44.4
24.8
16.5
.406
1982...........
4.0
10.0
16.5
24.5
45.0
17.0
.412
holds and how these proportions have
1983...........
4.0
9.9
16.4
24.6
45.1
17.1
.414
changed over time. Table 1 presents the
1984...........
4.0
9.9
16.3
24.6
45.2
17.1
.415
shares of aggregate income received by
19853..........
3.9
9.8
16.2
24.4
45.6
.419
17.6
1986 ...........
3.8
9.7
16.2
24.3
46.1
18.0
.425
each fifth, or quintile, of the household
1987...........
3.8
9.6
16.1
24.3
46.2
18.2
.426
income distribution for the entire 19671988...........
3.8
9.6
16.0
24.3
46.3
18.3
.427
93 period. The Gini index of income con
1989...........
3.8
9.5
15.8
24.0
46.8
18.9
.431
centration, a summary measure of in
1990...........
3.9
9.6
15.9
24.0
46.6
18.6
.428
come inequality, is also presented.11
1991 ...........
3.8
9.6
15.9
24.2
46.5
18.1
.428
Generally speaking, the table shows
1992...........
3.8
9.4
15.8
24.2
46.9
18.6
.433
19924..........
3.8
9.4
15.8
24.2
46.9
18.6
.434
that from the end of the 1960’s to the end
19935..........
3.6
9.1
15.3
23.8
48.2
.447
20.0
of the 1980’s, the share of income going
19936..........
3.6
9.0
15.1
23.5
48.9
21.0
.454
to the households in the highest quin
tile increased, while the shares going to
11mplementation of weights derived from 1970 population census.
2Implementation of weights derived from 1980 population census.
the lower quintiles declined or changed
3 Upper limit for earnings from longest job or business raised to $299,999; upper limits for other
very little. The dividing line between the
income items also raised.
top of the fourth quintile and the bottom
4Implementation of weights derived from 1990 population census.
of the fifth increased from $47,136 (in
5Upper limits in effect in 1992 applied to 1993 income data.
1993 dollars) in 1967 to $60,280 in
6Introduction of casic; upper limit for earnings from longest job or business raised to $999,999; upper
limits for other income items also raised. (See footnote 9 in text.)
1993.
The Gini indexes indicate that the
long-run trend toward greater income in
tween 1992 and 1993. The last time a change was made on
equality did not occur smoothly over the 1967-93 period.
this top code was in March 1986, for the survey year 1985,
Indeed, as shown in chart 1, the trend was very gradual from
when it was raised from $99,999 to $299,999.
1967 to 1979. Between 1979 and 1989, however, the index
grew rapidly—from .404 to .431—after which it slowed, end
ing at .433 in 1992.12
Trends in inequality
The slowing growth of household income inequality was
Chart 2 depicts how the Nation’s household income distri
no doubt related to the winding down of the economic ex
bution changed between 1967 (in 1993 dollars) and 1993.10
pansion of the 1980’s and the ensuing recession in the early
Clearly, there was a shift to the right, with greater propor
1990’s. This slowdown received little attention in the media
tions of households in 1993 having incomes above $50,000
and in the research community, but developments during the
than in 1967 (28.8 percent, compared with 16.8 percent), a
period can help one gain an understanding of the apparent
much smaller proportion with incomes between $15,000 and
surge in inequality between 1992 and 1993.
Table 1.1 Shares of aggregate household income received by each fifth and top
5 percent of households, 1967-93
64
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Federal Reserve Bank of St. Louis
August
1995
Table 2 presents real mean household incomes for each
quintile (as well as households in the top ventile) of the in
come distribution for the years 1979, 1989, 1991, 1992, and
1993, as well as the annual rates of change between each
succeeding pair of years. Chart 3 displays the annual rates of
change. The statistical cause of the rise in inequality in the
1980’s can be seen quite easily: mean household incomes for
the richest 20 percent of households were increasing by 1.7
percent a year, compared with a 0.4-percent increase for the
poorest 20 percent.
The situation in the 1989-91 period stands out in stark
contrast to that in 1979-89. During 1989-91, mean house
hold incomes plummeted, not only for the lowest quintile,
but also for those quintiles in the middle and at the top of the
distribution. The mean household income in the highest
ventile slid by almost 5 percent a year. The impact of corpo
rate downsizing and restructuring was particularly severe
among white-collar workers.13 Ironically, the collapse of in
comes across the distribution in this period halted the rise in
income inequality.14 (See chart 1.)
By 1992, the economy was slowly beginning to recover
from the recession. Mean household income remained virtu
ally unchanged between 1991 and 1992, but not for all house
holds in the distribution. In particular, mean incomes of
households in the bottom three quintiles continued to de
cline, while those of the top 5 percent continued to grow
(although the increase was not statistically significant). This
difference in income growth, however, helped push the Gini
index up from .428 to .433, and although it was not a statis
tically significant change, it perhaps was a signal of things
to come.
The change in inequality in the 1992-93 period is con
siderably more difficult to interpret, because of the afore
mentioned technical changes in the CPS. Some of the effects
of the changes, however, are quantifiable and are presented
in table 1. With respect to the reweighting of estimates as a
result of the 1990 decennial census, the impact on measur
ing inequality was minimal. As shown in the table, the 1992
income shares and Gini indexes have been calculated using
both 1980 and 1990 population weights. Shares were unaf
fected in 1992, and the Gini index was only slightly differ
ent (rising from .433 to .434, but not a statistically signifi
cant change).
Increasing the upper limits, or top codes, in 1993, how
ever, had a significant impact both on the Gini index and on
the shares of aggregate income received by various quintiles
of the distribution, as can be seen in the table. If the new top
codes had been used, the Gini index for 1993 would have
been .454 instead of .447— .020 point higher than the 1992
Gini, instead of .013 point higher. Using comparable top
codes between 1992 and 1993, however, preserved some ana
lytical comparability between years.
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Table 2.
Mean income of each fifth and top 5 percent of
the household income distribution, 1979, 1989,
1991,1992, and 1993
[In 1993 dollars]
Lowest
fifth
Second
fifth
Third
fifth
Fourth
fifth
$7,823
8,182
7,706
7,547
$19,457
20,278
19,255
18,828
$32,079
33,707
$84,484
$128,847
99,669
93,501
7,506
7,411
18,725
18,647
31,716
31,548
31,260
$47,076
50,986
48,758
48,649
48,429
48,572
94,233
93,837
98,589
161,030
145,913
149,592
148,937
163,228
0.4
-3.0
0.4
-2.6
0.5
-2.6
0.8
-2.2
1.7
-3.2
-4.9
1991-92s
-2.1
-2.2
-.8
-.2
.8
1992-93
-1.3
-.4
-.9
.3
5.1
Year
1979.....
1989.....
1991 .....
19921....
19922....
19933....
31,984
Highest
Top
fifth
5 percent
Annual
rate of
change
(percent):4
1979-89
1989-91
2.2
2.5
9.6
1Survey weights derived from 1980 population census.
2Survey weights derived from 1990 population census.
3Introduction of casic; upper limits in 1993 are the same as in 1992.
4Compounded.
5Change based on income data using 1980 weights.
Chart 3 and table 2 show the percent changes in mean
household incomes across quintiles (and in the top ventile)
for the 1992 and 1993 distributions, both of which are
weighted according to 1990 population controls, and both of
which use the upper income limits of 1992. Incomes in the
top ventile rose from $149,000 to $163,000, or almost 10
percent. The highest quintile’s mean income increased by
5.1 percent, from $94,000 to almost $99,000. In contrast to
the further declines in mean incomes in the bottom and third
quintiles, these very sizable increases pushed inequality up,
as measured by Gini index, by the largest amount for 1 year
since the statistical series on household income inequality
began.
The question, of course, remains: even after controlling
for changes in the weighting of the income data and for top
coding between 1992 and 1993, how much of the increase
was due to the new mode of data collection (CASIC), and how
much was due to changes taking place in the economy?
Survey changes or economic changes?
Attempts to quantify or decompose the effects of various fac
tors on changes in survey data are a common exercise among
economists and other researchers. Several statistical proce
dures are available for estimating such effects. In the case of
Monthly Labor R eview
A ugust
1995
55
Income Inequality
the apparent surge in income inequality between 1992 and
1993, however, the potential source of the change arises
not only from factors outside the survey (that is, the
economy), but also from factors inside the survey (for ex
ample, the data collection methodology). Untangling these
potential effects, therefore, is even more challenging and,
for the purposes of this article, will consist simply of draw
ing inferences from evidence relating to changes in the
quality of the data and evidence relating to changes in the
nature of job growth.
Changes in the quality of the data. Because the rede
sign of the monthly CPS was so extensive, the Census Bu
reau and the Bureau of Labor Statistics went to great
lengths to assess the impact of the changes on the monthly
estimates of employment and unemployment.15The results
of their evaluation suggested that the national unemploy
ment rate would be 0.5 percentage point higher in 1993
based on a parallel survey using the new questionnaire
and technology than it actually was using the old ques
tionnaire and collection methods.16 Since that time, how
ever, b l s has reexamined the effects of the changes and
Chart 3.
found them to be less (0.2 percentage point), but the Agency
continues to warn data users about the possible effects of the
changes on the estimates.17The assessment of c a s i c ’s impact
on the income data collected in the March 1994 CPS Annual
Demographic Supplement, on the other hand, was much more
lim ited, because only the mode of collection had been
changed.18Basically, aspects of data quality were examined.
One of the most important reasons for computer-assisted
interviewing is to simplify the job of the interviewer. The com
puter automatically brings the appropriate questions to the
screen, it can be programmed to perform editing functions and
identify inconsistent answers, and it has the ability to store and
display data from earlier interviews. With these advantages,
however, come certain disadvantages, such as a breakdown or
malfunction of the computer, interviewer errors in recording
responses, and, in those households in which a laptop com
puter was used in the home, the possible inhibiting influence
on respondents of the computer’s presence.
In reviewing the income data that were collected in March
1994, it was observed that certain income estimates were sig
nificantly lower than the previous year’s estimates. Further re
view found that an unusually large number of subannual (that
Annual rates of change in real mean household income, by quintiles and top 5 percent,
1979-89,1989-91, 1991-92, and 1992-93
Percent change
Percent change
10
5
0
-5
-10
Note: Annual rates of change for 1 9 7 9 -8 9 and 1989-91 are average annual rates; 1 9 9 2 -9 3 changes are based on 1990 weights.
56
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Federal Reserve Bank of St. Louis
August
1995
is, weekly or monthly) income amounts were being recorded.
improvements were statistically significant in the earnings
Lack of familiarity with the new technology on the part of
classes below $50,000 and between $75,000 and $99,999.
the interviewers was the suspected cause of the problem. To
The lowering of this rate is probably the result of the smooth
correct for those income recipients with unusually low
er transition between the monthly portion of the CPS and the
amounts, reinterviews were conducted in August 1994, and
supplemental questions as a result of CASIC.
the incorrect amounts were adjusted.19 Other than this find
Reaching any firm conclusion about the impact of CASIC
ing, the evidence with respect to the quality of the data was
on the quality of the income data after examining these esti
inconclusive. The Census Bureau, however, warned users that
mates is difficult because the evidence is mixed: imputations
the data from the March 1994 CPS would “not [be] strictly
by item increased, but overall imputations declined. In addi
comparable to [data from] earlier years.”20
tion, the fact that there was no discernible pattern across earn
Another aspect of the quality of the data that has been
ings classes lends further support to the notion that CASIC’s
examined involves the imputation of information on income
impact on the income data was inconclusive.
that occurs because a response to a question about income
was not forthcoming. Table 3 presents information on this
Changes in the nature of job growth. Research into the
issue. For persons with earnings (wages and salaries, or in
causes of rising inequality of incomes among households in
come from self-employment, or both) from their longest job
recent years has generally focused on changes taking place
or business in 1992 and 1993, the table shows the propor
in the Nation’s economy— specifically, changes in the wage
tions that (1) actually reported their earnings from their long
distribution. This is because labor market earnings repre
est job or business, or (2) had only their earnings from their
sent such a large part of aggregate household income.
longest job or business imputed, using the Census Bureau’s
As has been well documented, the wage distribution has
“hot deck” procedure, or (3) had all information on them
grown more unequal over time, just as the income distribu
imputed in the Annual Demographic Supplement, including
tion has. Shifts in labor demand toward more highly skilled
earnings from their longest job or business.21 These propor
and well-educated workers within industries and away from
tions are displayed by broad earnings classes to see whether
workers with relatively poorer skill endowments are thought
differential effects were evident.
to be responsible for this development.22 Technological
For many households, of course, the earnings of persons
changes in the production of goods and services that are “skill
from their longest jobs or businesses represents the largest
biased” are thought to underlie these shifts.
part of household income and should be a fairly good indica
The impact of this economic development on growing in
tor of the quality of the household income data. Table 3 shows
come inequality has been compounded by societal changes
that there was a slight overall decline from 1992 to 1993 in
in living arrangements. The well-known rise in single-par
the proportion of individuals who actually reported their
ent households over the last couple of decades has increased
earnings to Census Bureau interviewers—from 79.6 percent
income dispersion because single-parent households tend to
to 77.7 percent. By earnings classes, changes in the propor
have much lower incomes than married-couple households
tions of persons who actually reported their earnings were
do.23 In addition, to the extent that growing proportions of
statistically significant, with the lone exception of those with
men and women with similar skill profiles, and therefore
earnings of $75,000 or more.
A significant increase took place from
1992 to 1993 in the proportion of per Table 3. Percent of persons with earnings from longest job or business whose
earnings were actually reported, item imputed, or totally imputed, by
sons who had only their earnings from
earnings, 1992 and 1993
the longest job or business imputed—
Item imputed
Reported
Totally imputed
from 9.3 percent to 12.8 percent. How
Earnings
1992
1993
1992
1993
1992
1993
ever, all earnings classes experienced
significant increases in imputations by
Total.............................
79.6
77.7
9.3
12.8
11.1
9.5
item. High earners—those with earnings
Less than $25,000...........
79.5
9.2
9.7
77.0
13.3
11.3
of $100,000 a year or m ore— had a
$25,000 to $49,999..........
80.3
79.7
8.9
10.7
11.3
9.0
higher rate of imputation by item than
$50,000 to $74,999..........
10.4
79.6
78.1
10.0
12.3
9.6
$75,000 to $99,999..........
75.5
11.2
76.0
14.9
9.2
13.3
did any of the other earnings groups—
$100,000 or m ore............
73.2
17.4
70.8
14.3
12.4
11.8
17.4 percent.
The proportion of earners who had all
their work experience and income infor
N ote : Estimates are based on weighted counts of earners in 1992 and 1993; weights are derived
from 1990 population census.
mation imputed declined from 11.1 per
cent in 1992 to 9.5 percent in 1993. The
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57
Inco m e Inequality
P ercen t distribution o f Dersons with w o rk e x o e r ie n c e . b v ho urlvr e a rn
in a s
.......^
and household income, 1979 and 1993
Hourly
earnings
Total
Less than
$14,000
$14,000 to
$27,999
$28,000 to
$41,999
$42,000 to
$55,999
$56,000
or more
Total .........................
100.0
7.2
17.7
22.0
19.8
33.2
1979 (in 1993 dollars)
Less than $ 7 .0 0 .......
31.0
5.6
7.6
6.3
4.5
7.0
$7.00 to $13.99........
38.5
1.3
9.0
9.9
7.9
10.3
$14.00 to $20.99......
18.7
.2
.7
5.2
5.2
7.4
$21.00 to $27.99......
6.7
.1
.2
.3
1.9
4.2
$28.00 or m o re ........
5.1
.2
.2
.2
.3
4.4
Total .......................
100.0
8.1
18.3
20.4
17.3
35.8
Less than $ 7 .0 0 .......
32.9
6.7
QO
6.8
4.0
6.3
$7.00 to $13.99........
36.7
1.1
qq
9.3
7.6
10.0
1993
$14.00 to $20.99......
17.5
.2
.6
3.6
4.0
9.1
$21.00 to $27.99......
6.8
.1
.1
.3
1.2
5.1
$28.00 or m o re ........
6.1
.1
.2
.3
.3
5.3
Note: Due to rounding, totals may not equal sums of individual items.
earnings, tend to marry and work, they also produce disper
sion in the income distribution.24 By themselves, however,
changes in living arrangements occur only over long periods
of time and were not likely to have any appreciable effect on
the apparent surge in income inequality between 1992 and
1993.25 Rather, most of the surge is likely to be related to
changes in the nature of the employment growth that oc
curred during the period.
Some perspective on the nature of employment growth
between 1992 and 1993 can be obtained by comparing that
growth with what happened in the 1979-89 and 1989-92
periods. Table 4 shows the distribution of persons with some
work experience in 1979 and 1993, cross-classified by their
average hourly earnings and the annual income of the house
hold in which they lived.26The table relates to all workers—
from those who worked only a few weeks at part-time jobs to
those who worked year round at full-time jobs. The data can
be summarized by focusing on three broad groups account
ing for approximately 75 percent of all persons with work
experience in both years:
• Persons with hourly earnings of less than $7 and house
hold incomes of less than $42,000 a year
• Persons with hourly earnings between $7 and $27.99 and
annual household incomes between $14,000 and $56,000
• Persons with hourly earnings of more than $14 and yearly
household incomes of $56,000 or more.
58
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As is known, both earnings and in
come inequality rose between 1979 and
1993, and the changes in the proportions
of persons in these groups help to ex
plain why. Low-earning workers from
households with incomes of less than
$42,000 a year increased from 19.5 per
cent to 22.7 percent of all workers, those
with midlevel earnings and income de
clined from 39.1 percent to 34.3 percent
of the total, and those with hourly earn
ings from the middle to high range who
lived in high-income households in
creased from 16.0 percent to 19.5 per
cent of all workers. In other words, the
table shows the much-talked-about shift
of middle-earnings employment away
from middle-income households to lowincome households and especially highincome households. (It is interesting to
note that about 10 percent of all workers
earned less than $7 an hour, but were
from households with incom es of
$42,000 a year or more.)
Table 5 presents the average annual
changes that occurred in these broad
earnings-income groups from 1979 to 1989, 1989 to 1992,
and 1992 to 1993. The table shows that between 1979 and
1989 employment was growing rapidly—by 1.8 million per
sons a year. Much of the increase in average annual employ
ment was taking place among persons with middle to high
earnings who lived in high-income households. Employment
in this earnings-income category was rising, on average, by
about 921,000 persons a year during the 1980’s. Employ
ment was also growing, however, at the other end of the earn
ings-income distribution. The employment of workers with
low hourly earnings who were from households with incomes
of less than $42,000 a year increased by about 494,000 per
sons per year. But among workers with middle-level earn
ings who were from middle-income households, employment
growth was meager at best—35,000 persons a year. The fol
lowing tabulation presents Gini indexes for earnings alone
for selected years from 1979 to 1993 (the figures in paren
theses are the years of population censuses from which the
survey weights for the given years are derived):
Year
Gini index
1979 (1 9 8 0 )........... ...................385
1989
1992
1992
1993
(1980)........... ...................428
(1 9 8 0 )........... ...................414
(1 9 9 0 )........... ...................414
(1990)........... ...................449
(817,000 per year) and workers in the
middle of the earnings and income dis
tribution (342,000). These net changes
[In thousands]
actually produced a decline in earnings
Hourly
Less than $14,000 to $28,000 to $42,000 to
$56,000
inequality: the Gini index was .428 in
Total
earnings
$14,000
$27,999
$41,999
$55,999
or more
1989 and .414 in 1992.
The 1992-93 period represented a re
1979-89
turn
to the pattern of employment growth
Total ........................
1,756
116
187
132
74
1,248
of the 1980’s, but in a more extreme way.
Table 5 shows that the employment
Less than $7.00.........
602
152
217
125
39
68
growth of persons with middle to high
*~9
$7.00 to $13.99..........
361
-28
82
58
258
earnings who were from high-income
$14.00 to $20.99........
340
-6
-16
-48
-22
433
households rose by 949,000 during that
$21.00 to $27.99........
201
0
-3
-2
-26
232
$28.00 or m ore..........
252
period. At the same time, however, there
-3
-2
-1
1
256
was only modest employment growth
1989-92
among persons with low earnings who
Total...........................
310
465
663
120
168
-1,106
were from low- to middle-income house
holds—about 317,000 persons. And, as
Less than $7.00.........
603
381
71
296
140
-284
in the 1980’s, persons in the middle earn
$7.00 to $13.99..........
366
56
291
77
182
-241
ings and income group experienced no
$14.00 to $20.99........
-212
15
56
-113
4
-174
employment growth. (The group actually
$21.00 to $27.99........
-203
-2
2
9
-99
-112
lost 53,000 workers.) The Gini index for
$28.00 or m ore..........
-244
15
18
8
10
-295
these workers’ earnings distributions
1992-93
shot up from .414 to .449 between 1992
and
1993, and although 1-year changes
Total...........................
1,459
-21
290
545
-721
1,366
should obviously be viewed with caution,
Less than $7.00.........
421
it is clear that this development was re
-183
380
-425
120
530
$7.00 to $13.99..........
510
86
flected in the apparent surge in income
-77
699
-85
-113
$14.00 to $20.99........
-424
38
-45
-316
inequality.
-299
199
$21.00 to $27.99........
246
23
0
-25
25
222
According to these data, then, the pat
$28.00 or m ore..........
706
16
33
66
63
528
tern of employment growth in the 199293 period represented not only a return
to the pattern seen in the 1980’s, but an
N ote : Data for 1992 and 1993 use survey weights from the 1990 population census. Due to rounding,
totals may not equal sums of individual items.
exaggeration of that pattern. While the
ratio of employment growth at the top
During the 1979-89 period, the Gini index based on these
end of the distribution to that at the bottom end averaged
workers’ earnings distributions increased from .385 to .428,
about 1.86 to 1 in the 1980’s, in the 1992-93 period it was
reflecting the foregoing annual average net changes in
2.99 to 1. This development may have been the result of the
employment.
combined effect of the return to the work force of many highly
Table 5 also presents data for the recession that took place
paid workers who were laid off in the early 1990’s along
between 1989 and 1992. The annual average net change in
with the resumption of the secular trend toward job creation
employment during that period was much less than that of
at both ends of the wage distribution with little growth in the
the previous period—only 310,000 persons a year—and there
middle.
were noticeable differences in where employment was grow
ing. Employment declined, on average, by 581,000 persons
Conclusions
for those with middle to high earnings who were from highincome households. This decline reflected not only the loss
The result of efforts to improve the quality of economic data
of many high-paying blue-collar jobs as a result of the reces
oftentimes is like a two-edged sword: on the one hand, the
sion, but also a reduction in employment of high-paying
data are improved, but on the other, the comparability of the
white-collar jobs.
improved data with previously collected data comes into
In contrast, employment gains were recorded among lowquestion. Such is the situation confronting those examining
earning workers in low- to middle-income households
the change in income inequality between 1992 and 1993.
Table 5.
Annual average net change in persons with work experience, by
hourly earnings and household income, 1979-89, 1989-92, and 1992-93
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59
Incom e Inequality
This article has discussed, in an inferential way, one pos
sible interpretation of the change. It does appear that the re
ported surge in income inequality was driven by an unusu
ally large increase in incomes in the highest quintile of the
distribution—especially the top 5 percent of households.27 An
examination of the effects of the introduction of c a s i c
on the data showed that incomes of a certain number of house
holds had been misrecorded, but that this misrecording
affected only households in much lower income ranges.
Imputation rates also were examined, especially at the high
end of the distribution, but the changes there did not indicate
any greater inclination on the part of high earners to report
their earnings. For those who did report, however, it was ap
parent that considerably greater earnings were being reported,
given the overall increase in incomes at the top end of the
distribution. Whether or not the use of the computer in the
survey process caused those who reported their earnings and
incomes to be more forthcoming than usual is, unfortunately,
a difficult hypothesis to test.
Evidence was shown that the increase in inequality could
have been induced by changes taking place in the nature of
employment growth as the economy moved out of the reces
sion. Very strong employment gains were registered among
persons with middle to high earnings who lived in high-in
come households. With the return to work at full capacity of
many highly paid white-collar workers caught in the reces
sion of the early 1990’s, and with the resumption of the “twotiered” employment growth characteristic of the 1980’s, the
forces for greater income inequality may have been particu
larly strong between 1992 and 1993. It remains for us to await
the data from the March 1995 CPS to obtain more evidence
on how to apportion the 1992-93 changes in household in
come inequality between changes in survey techniques and
changes in the nature of employment growth.
□
Footnotes
1See “Census Bureau Announces Number o f Americans in Poverty Up for a
Fourth Year although Poverty Rate Unchanged; Household Income and Health
Care Coverage Drop,” United States Department of Commerce News, C B 94159 (Bureau o f the Census, Oct. 6, 1994). See also Daniel H. Weinberg, press
briefing statement on the 1993 income and poverty estimates (Bureau of the
Census, Oct. 6, 1994).
2 See Paul Krugman, “Long-Term Riches, Short-Term Pain,” The New York
Times, Sept. 25, 1994, p. F9.
3The Gini index is a bounded measure of income inequality that ranges from
0 (all households receive the same share o f aggregate income) to 1 (one house
hold receives all income). There are many other measures o f inequality, such as
the ratio o f incomes o f households at the 90th percentile of the distribution to
those o f households at the 10th percentile, the variance of the logarithms of
incomes, the coefficient o f variation, the Theil index, and so on. While all of
these measures are constructed differently and have different properties, each
has indicated a growing dispersion in household income distribution in recent
years.
4See Weinberg’s press briefing statement, p. 5.
5 See “Nature o f Employment Growth Examined by
410 (Bureau o f Labor Statistics, Aug. 24, 1994), p. 2.
b l s
,”
n e w s
,
u sd l
94-
6 See “Money Income o f Households, Families, and Persons in the United
States: 1992,” Current Population Reports, Consumer Income, Series P 60184 (Bureau o f the Census, September 1993), p. C-12.
7 See Rudy Fichtenbaum and Hushang Shahidi, “Truncation Bias and the
Measurement o f Income Inequality,” Journal of Business and Economic Sta
tistics, vol. 6, no. 3, July 1988, pp. 335-37.
8 For a further discussion of these changes, see “Money Income o f House
holds, Families, and Persons: 1993,” Current Population Reports, Consumer
Income, Series P60-188 (Bureau of the Census, forthcoming).
9 Other top codes that were increased were earnings from all other jobs or
businesses (from $99,999 to $999,999), income from Social Security (from
$29,999 to $49,999), Supplemental Security Income (from $9,999 to $24,999),
public assistance (from $19,999 to $24,999), and veteran’s benefits (from
$29,999 to $99,999). Top codes appearing in c p s public-use data files, how
ever, were not changed and are lower than pre-1993 top codes. For example, the
top code on the public-use file for earnings from the longest job or business is
$99,999.
10 All income data in this article have been adjusted for inflation using the
experimental consumer price index for all urban consumers, abbreviated
bls
C P 1 -U -X 1 .
11 Two facts about the measurement of income inequality should be men
tioned in this context. First, all measures of inequality have certain limitations
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embodied in them. The Gini index, which is a summary measure, can obscure
the location in the income distribution where changes are occurring. A concep
tually more difficult problem occurs when Lorenz curves, from which the Gini
index is derived, cross. Lorenz curves show the relationship between the cumu
lative percentage of aggregate income and the cumulative percentage of recipi
ents, and when the curves intersect for different years (or countries, groups, and
so forth), a condition of Lorenz dominance prevails that makes it impossible to
determine which distribution o f income is more unequal.
Second, researchers who study income inequality and who focus more di
rectly on the welfare implications of their findings customarily adjust the house
hold or family income data for differences in the number of household or family
members because o f presumed economies o f scale. No such adjustments were
made to the data reported by the Census Bureau, nor were they made to the data
used in this article; and even if they were made, they would not substantively
change the findings presented.
12 Actually, the slowdown began in 1987. The change in the Gini index
between 1987 and 1989 was not statistically significant, nor was the change
between 1989 and 1992. Changes in estimates are statistically significant un
less otherwise stated.
13 See Joseph Meisenheimer II, Earl Mellor, and Leo Rydzewski, “Job mar
ket slid in early 1991, then struggled to find footing,” Monthly Labor Review,
February 1992, pp. 3-17, especially p. 14; and Jennifer M. Gardner, “The 199091 recession: how bad was the labor market?” Monthly Labor Review, June
1994, pp. 3-11.
14Income growth patterns in the five quintiles during the 1987-88 and 1988—
89 periods were also more uniform than in the 1979-87 period, and income
inequality was virtually unchanged in the first two periods.
15For a discussion of the two Agencies’ evaluation plan, see Chester E. Bowie,
Lawrence S. Cahoon, and Elizabeth A. Martin, “Overhauling the Current Popu
lation Survey: Evaluating changes in the estimates,” Monthly Labor Review,
September 1993, pp. 29-33.
16See Sharon R. Cohany, Anne E. Polivka, and Jennifer M. Rothgeb, “Revi
sions in the Current Population Survey Effective January 1994,” Employment
and Earnings (Bureau of Labor Statistics, February 1994), pp. 13-37.
17See “Statement of Katharine G. Abraham, Commissioner, Bureau o f La
bor Statistics, before the Joint Economic Committee, United States Congress,”
Dec. 2, 1994, p. 4.
18 “Money Income: 1993.”
19A total 5,422 cases were targeted for reinterview, and 3,634 of those were
completed. A proportion o f the cases that were targeted but not reinterviewed
had their income amounts adjusted on the basis of likelihood functions derived
from completed reinterviews. See “Money Income: 1993.”
20 “Money Income: 1993.”
21 For a discussion of the “hot deck” method of imputation and recent changes
to it, see Edward J. Welniak, Jr., “Effects of the March Current Population
Survey’s New Processing System on Estimates o f Income and Poverty,” paper
presented before the 1990 meeting of the American Statistical Association, Ana
heim, California, Aug. 2,1990.
22 See Lawrence F. Katz and Kevin M. Murphy, “Changes in Relative Wages,
1963-1987: Supply and Demand Factors,” Quarterly Journal of Economics,
February 1992, pp. 35-78; and John Bound and George Johnson, “Changes in
the Structure o f Wages in the 1980’s: An Evaluation of Alternative Explana
tions,” American Economic Review, June 1992, pp. 371-92.
23 See, for example, Lynn Karoly, “The Trend in Inequality among Families,
Individuals, and Workers in the United States: A Twenty-Five Year Perspec
tive,” in Sheldon Danziger and Peter Gottschalk, eds., Uneven Tides: Rising
Inequality in the 1980s (New York, Russel Sage Foundation, 1993); and Paul
Ryscavage, Gordon Green, and Edward Welniak, “The Impact of Demographic,
Social, and Economic Changes on the Distribution of Income,” in Studies in
the Distribution of Income, Current Population Reports, Consumer Income,
P60-183 (Bureau o f the Census, October 1992).
24 See Lynn A. Karoly and Gary Burtless, “The Effects of Rising Earnings
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Inequality on the Distribution of U.S. Income,” Dec. 20,1993 (mimeograph).
25 It is interesting to note that, while the proportion of all households that
were maintained by single parents was 15.7 percent in 1992 and 15.8 percent in
1993, the proportion o f all families in which a wife was in the paid labor force
increased from 46.0 percent to 47.0 percent.
26 Average hourly earnings were obtained by dividing the annual earnings
(wages and salaries, as well as self-employment income) of those workers by
the product of the number o f weeks and the usual number o f hours per week
they worked. Although this technique for estimating annual hours is crude
because it involves usual, and not actual, hours worked (as well as having other
problems), the resulting estimates are sufficiently reliable for the purpose of the
intended comparison. The 1979 data are weighted according to 1980 weights,
and the 1993 data are weighted according to 1990 weights.
27 According to early estimates from the Internal Revenue Service for 1993,
the number of tax returns with adjusted gross incomes of $ 100,000 or more was
3,557,000. This was 7.4 percent more than the figure for 1992 (3,312,000).
The number of returns increased by 0.4 percent. (See SO/ Bulletin, vol. 14, no.
2 (Internal Revenue Service, Fall 1994), p. 20; and SOI Bulletin, vol. 13, no. 2
(Internal Revenue Service, Fall 1993), p. 24.
LABSTAT Available via World Wide Web
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l a b s t a t Public Access has introduced a new production Internet service over the
World Wide Web. b l s and regional offices programs are described using hypertext
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M onthly Labor Review
August
1995
61
Textile, Apparel E m p lo y m e n t*
Unraveling em ploym ent trends
in textiles and apparel
Both of these industries continue
to shed large numbers of workers;
although textiles and apparel are closely related,
the reasons for their job losses,
and the prognosis for their future, differ
Lauren A. Murray
Lauren A. Murray is an
econom ist form erly with
th e Division o f M onthly
Industry Em ploym ent
Statistics, Bureau of
Labor Statistics.
he U.S. textiles and apparel industries
employ about 1.6 million U.S. workers—
1 in 10 manufacturing workers and more
than the auto and aircraft industries combined.1
Textiles and apparel reached employment peaks
long ago and both have been influenced by simi
lar forces, including productivity, foreign trade,
competition and business cycles. While employ
ment losses have affected the two industries, the
duration and depth of those losses differ.
The textiles industry produces base products
such as threads, yarn, and cordage and woven
fabrics, carpets, and rugs; in contrast, the ap
parel industry produces finished clothing prod
ucts made from base fabrics. Employment in the
textiles industry peaked in 1948, 25 years be
fore the apparel industry. The textiles industry
has lost one-half of its employment base since
its peak level; the apparel industry has trimmed
one-third of its jobs since its peak in 1973. And
since 1970, the industries have lost 30 percent
of their combined work force; in the current
expansion, the industries have failed to par
ticipate in the strong cyclical growth that has
been prevalent in much of manufacturing. (See
table 1.)
Although the textiles and apparel industries
are closely related, different reasons account for
their respective job losses. Both industries will
continue to face intense global competition in
the current decade, and, while some manufac
turers may become more profitable, employment
will most likely continue to fall.
T
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This article focuses on the employment trends
in textiles and apparel over the past half cen
tury, with an emphasis on developments since
the 1970’s. The underlying causes of the pro
tracted employment declines in each industry are
examined and some of the issues that will affect
future employment needs are discussed.
Long-term trends
Em ploym ent in the U.S. textiles industry
reached an all-time high of 1.3 million jobs in
June 1948, reflecting the overwhelming domi
nance of the United States in the world economy
following World War II. Employment subse
quently declined through several business cycles,
with new levels rarely returning to 1 million.
However, this long-term decline in employment
is not reflected in a corresponding drop in pro
duction. On the contrary, production increased
by nearly 190 percent between 1948 and 1994
while employment dropped by nearly 50 per
cent.2 (See chart 1.) Labor productivity grew by
180 percent in the textiles industry between 1950
and 1973.3 In contrast, the apparel industry ex
perienced productivity growth of only 73 per
cent during that same period, which was more
in line with total manufacturing labor produc
tivity growth of 84 percent. Thus, labor produc
tivity growth in the textiles industry was twice
the rate of all of manufacturing, while labor pro
ductivity growth in the apparel industry lagged
behind other manufacturing.
The apparel industry’s all-time peak employment level of
1.4 million occurred in April 1973. (See chart 2.) The level
of apparel employment appears to have been greatly influ
enced by the amount of apparel imports entering the United
States. Beginning in the 1960’s, imports of apparel products
increased rapidly and gained a larger share of the domestic
market, contributing to the subsequent employment declines
in the industry. In the early 1960’s, imports comprised about
2 percent of domestic consumption; by 1980 the proportion
had risen to nearly 15 percent,4 and in 1988 it was 26 per
cent. (See chart 3.)
Since its peak in 1973, the long-term employment trend
of the apparel industry has closely followed that of the tex
tiles industry. Through successive business cycles, apparel
manufacturers failed to fully recover jobs lost during down
turns. Moreover, underscoring the industry’s long-term, noncyclical decline, periods of employment growth have been
shorter, while the periods of job loss have become more per
sistent. The most recent employment contraction lasted 7
years and followed a growth cycle of only 16 months. The
industry lost 220,000 jobs between its April 1984 peak and
April 1991 recession trough, while productivity increased
by 13 percent and imports continued to expand.
The textiles industry
Increased spending by textile manufacturers in the 1970’s
set the stage for productivity advances that occurred in the
1980’s. The increased spending boosted productivity levels
substantially, which helped manufacturers compete with ris
ing imports. Several recessions, combined with continued
technological advances and rising imports, produced a pe
riod of rapid employment losses.
Productivity and structural changes. In the late 1960’s and
early 1970’s, textiles manufacturers made major strides in
automation. Although the industry has historically spent con
siderable amounts of money on capital investments, spend
ing in the 1970’s was significant because most of it was in
vested in radical new technologies. Before 1968, the primary
source of productivity gains was decreased manual handling
of materials.5 For more than 100 years the industry had up
dated and modified existing machinery. But in the 1970’s,
completely new technology, such as open-end spinning and
shuttleless looms, became available. These technologies dras
tically reduced the time and number of workers needed to
produce fabrics. For example, a water- or air-driven shuttle
less loom not only produced fabric three times faster than its
wooden fly shuttle predecessor, but it also could produce
seven or eight times more fabric because it was able to weave
wider widths. Open-end spinning boosted the rate of pro
duction of yarn four times over the older ring-spinning tech
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Table 1.
Employment in apparel and textiles, selected
years, 1939-94
Apparel
Textiles
Employment
in
thounsands
Percent
change
1939..........
1949 ..........
1959 ..........
1969..........
1979..........
1,193.0
1,187.0
945.7
1,002.5
885.1
(’)
-0.5
-20.3
1989..........
1990..........
1991 ..........
1992..........
1993..........
1994..........
719.8
691.4
670.0
674.1
674.8
672.0
-18.7
-3.9
-3.1
Year
Employment
in
thousands
Percent
change
924.0
1,173.0
1,225.9
1,409.1
1,304.3
(’)
26.9
4.5
14.9
-7.4
1,075.7
1,036.2
1,006.0
1,007.2
984.6
954.3
-17.5
-3.7
-2.9
6.0
-11.7
.6
.1
-.4
.1
-2.2
-3.1
1 Data are not available.
ñique and reduced the number of steps involved in manu
facturing some kinds of yarn from 15 to 3.6
While the technology available was revolutionary, it also
was expensive. U.S textile manufacturers spent an average
of $3.1 billion (in constant 1987 dollars) annually between
1969 and 1974 on capital purchases, 90 percent of which
was for new equipment purchases. During the first half of
the decade, manufacturers spent between 6 percent and 7
percent of their value of shipments on capital investment. In
the latter half of the decade the spending dropped to about 5
percent of the value of shipments, or $2.4 billion annually.
During much of the 1970’s, capital expenditures for the in
dustry were greater than profits.7
As a result of the automation during the 1970’s, labor
productivity, expressed in terms of output per employee hour,
increased 56 percent between 1969 and 1979. Constant dol
lar shipments8 rose by $11.5 billion annually during the de
cade, while employment declined by more than 125,000jobs.
In the early and mid-1980’s, profits in the textile industry
began to decline dramatically due to the rising value of the
dollar, a substantial drop in exports of textile products, and
two recessions in the early 1980’s. Capital spending declined
to an average of $2.2 billion, and in 1986, fell to $1.8 bil
lion, its lowest level since 1963. In the mid-1980’s, textile
manufacturers took part in several mergers and acquisitions.
This restructuring led to the establishment of several domi
nant firms in the industry.9
Many textiles companies were the targets of leveraged
buyouts. Because the industry had a history of erratic earn
ings, many manufacturers’ stock was traded below book
value. Its low was attractive to buyers who were able to raise
capital by using the company’s assets as collateral. This was
the case for at least four major manufacturers: Cannon Mills,
Cone Mills, Dan River Inc., and Burlington, which were
purchased during the 1980’s. The size of the new firms lent
M onthly Labor Review
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63
Textile, Apparel Employment
itself to achieving greater economies of
scale, and gave the newly formed com
panies a larger capital base with which
to invest in emerging technologies. Capi
tal investments rebounded to an average
of $2.4 billion between 1987 and 1990.10
Between Decem ber 1978 and the
April 1991 employment trough, employ
ment declined 26 percent, or 230,000
jobs. Labor productivity gains averaged
2.7 percent a year between 1979 and
1991, more in line with total manufac
turing productivity growth of 2.6 percent.
Production grew even as employment
losses persisted, and reached a new alltime high in April 1989, before the most
recent recession began and demand
weakened. Following the 1990-91 reces
sion, the textile industry enjoyed 2 years
of employment growth before it again
began trimming payrolls in June 1993.
However, production continued to in
crease: December 1994 levels were 8 per
cent above the April 1989 peak level.
Chart 1.
Employment and production in textiles, 1950-94
Employment,
1987=100
Production,
1987=100
180
160
140
120
100
80
60
40
20
So u r c es : Employment data from the Bureau of Labor Statistics; production data
Imports and exports. A second reason
from the Federal Reserve Board
for the decline in textile employment was
increased imports. The textile industry
fared far better than the apparel industry against rising im
From 1980 to 1988, the import share of total U.S. textile
ports in the 1970’s. The textile industry not only kept its
consumption increased by less than 3 percentage points, ris
share of the domestic market throughout the decade, but it
ing to 7 percent of domestic consumption. In contrast, the
also maintained a trade surplus for the latter half of the de
apparel industry’s import penetration had reached 26 per
cade and into the early 1980’s. The ability of the industry to
cent by 1988, an increase of 13 percentage points from 1980.
maintain its market share was, very likely, due to the tech
In 1992, imports still accounted for a relatively small 11 per
nological advances that reduced needed labor and acceler
cent of all domestic textile consumption.
ated the production process. Capital expenditures required
Exports offset some of the increase in textile imports dur
to obtain this type of technology were prohibitive to many
ing the late 1980’s. Although exports fell during the first half
developing countries, particularly those with a large number
of the decade because of an overvalued dollar, they began to
of small, fragmented producers. Low wages in developing
rebound in 1986, providing some stimulus for the industry.
countries may also have limited pressures on those textile
In 1989, exports comprised 4 percent of industry shipments.
manufacturers to introduce new labor-saving technologies.11
The impact of exports on employment is even greater when
Thus, U.S. manufacturers were more competitive with the
indirect exports, such as the use of fabric in clothing that is
low-wage countries.
exported, is considered; neaily 10 percent of textile employ
The U.S. textiles industry also performed much better than
ment was related to direct and indirect exports in 1989.13
its European counterparts. The United States was the only
As was indicated above, the U.S. textiles industry does
major industrialized country to maintain its domestic mar
not appear to have greatly suffered from direct imports. How
ket share in the 1970’s; imports comprised only 4.5 percent
ever, the industry was significantly affected by the surge of
of domestic market share in 1970 and 1980. Germany’s and
apparti imports. The U.S. textile industry supplies most of
the United Kingdom’s textile import penetration increased
the textile products required by domestic apparel producers.
substantially. Import penetration by Japan, the largest postAs apparel imports rose and continued to gain domestic
World War II exporter, and Italy, while still posting a trade
market share, U.S. apparel producers required less domestic
surplus in the textiles industry, also increased.12
textile products.
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The apparel industry
Chart 2.
Employment and production In apparel, 1950-94
Employment in the apparel industry de
clined significantly in the 1970’s and
1980’s. Technology introduced in this
period was less revolutionary than that
in the textiles industry. Most likely, ap
parel imports had the principal influence
on employment. Apparel employment
peaked in 1973 with production peaking
in July 1987; both production and em
ployment have continued to decline in the
1990’s.
Productivity and structural changes.
Technological innovations in the apparel
industry during the 1970’s and 1980’s
were less sweeping and more incremen
tal than changes in the textiles industry.
Examples of technologies that were de
veloped in the 1970’s and 1980’s are pro
grammable sewing machines that allow
operators to work more than one machine
at a time, Computer Aided Design (CAD)
that reduces lead time, and computer con
trolled cutting of material. Labor produc
Sources : Employment data from the Bureau of Labor Statistics; production
data from the Federal Reserve Board.
tivity increased by 26 percent between
1969 and 1979; this was slightly less than
the 33-percent rate for all manufacturing.
low profit margin, and the cost of new, technologically ad
In the 1970’s, the apparel industry spent more on capital
vanced
equipment would be prohibitive to many of them. But
investments than it had during the 1950’s and 1960’s com
labor
productivity
continued to rise in the 1980’s as produc
bined. However, the industry still spent at only two-fifths of
tion
of
apparel
products
grew by 7 percent while employ
the textiles industry’s rate, primarily due to a lack of new
ment
fell.
Labor
productivity
grew at an annual average rate
technology. (See chart 4.) The new technology that was avail
of
2.4
percent
between
1979
and
1991.15 Yet it is impossible
able to apparel manufacturers was not as powerful or expen
to
know
if
employment
would
have
declined less without the
sive as that available to textile manufacturers. However, an
productivity
gains,
because
the
higher
labor costs would have
other reason for the low level of spending, and perhaps the
made
the
industry
even
less
competitive
with imports.
limited new technology available, can be explained by the
In
1990,
30
percent
more
labor
was
required for every
structure of the apparel industry: firms in the apparel indus
dollar
of
output
in
the
apparel
industry
than
in the textiles
try are typically smaller and more disconnected than firms
industry.1
6
The
textiles
industry
continued
to
invest
far more
in the textiles industry. For example, 23,600 domestic ap
in capital in the 1980’s than the apparel industry, spending
parel establishments employed about 1.3 million people in
$23 billion, or 4 percent of the industry’s value of shipments,
January 1976. By contrast, about 7,300 textile establishments
while the apparel industry spent only $8 billion, or 1.5 per
employed slightly more than 900,000 workers. Twenty-four
cent of that industry’s value of shipments. In addition, the
percent of textile workers were employed in establishments
apparel industry directed only half of those expenditures to
of more than 1,000 employees in 1976 compared with only 8
new equipment, while the textiles industry spent threepercent in the apparel industry; at the other extreme, nearly
fourths of its outlays on new equipment.
20 percent of apparel workers were employed in establish
ments of fewer than 50 workers, versus less than 7 percent
Imports and exports. Imports in the apparel industry in
of textile workers.14
creased from 5 percent of total consumption in 1970 to 26
The size of many apparel firms was often an obstacle to
percent in 1988, or from $1.3 billion to $22 billion annually.
large capital investments. Small firms typically operate on a
This contrasts with the textiles industry, which lost less mar
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M ontN y Labor Review
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65
Textile, A p p are l Em ploym ent
ket share to overseas productions. Ap
Chart 3.
Textile and apparel imports as a proportion of
parel imports not only grew rapidly, but
domestic consumption, 1970 and 1
comprised a large share of total sales.
This import growth led to large-scale em
1970
Textiles
1988
ployment declines.
The apparel industry was particularly
hard hit by imports from developing
countries. Less developed countries tra
ditionally have begun industrialization
with the apparel and textiles industries
because raw materials are relatively com
6.8
mon, and because the two industries re
quire less capital than most other manu
facturing activities.17 Thus, developing
countries with an abundance of cheap la
bor but very little capital can produce tex
tiles and apparel products.
An example of this type of industrial
ization policy can be seen in Japan fol
lowing World War II. Faced with the de
Apparel
struction of much of their manufacturing
(in percent)
base, the Japanese focused on the textiles
and apparel industries to rebuild. In
1950, textiles accounted for 24 percent
of total shipments and 48 percent of ex
ports. By 1980, the figures had dropped
to 5.2 and 4.8 percent. Textiles and ap
5.2
parel declined in importance as Japan
became more industrialized and wage
26.1
pressures grew. Japanese industrial
policy focused more on high technology
industries with larger profit margins.
Japanese textile producers today are simi
n
Domestic
lar to U.S. producers: they are more capi
| Imports
tal intensive, and they also manufacture
SOURCE: U.S. Department of Commerce
more expensive fabrics.
D eveloping countries rapidly in
creased their share of the world export market in apparel. In
for only 1.8 percent of world apparel exports), and grew
modestly in the latter half. But in contrast to the textiles
1965, world apparel exports totaled $3 billion and develop
industry, the apparel industry never experienced a trade sur
ing countries supplied only 14 percent; by 1991, world ap
parel exports totaled $119 billion and developing countries
plus. In 1989, exports accounted for only 4 percent of total
supplied 59 percent. The developing economies in Asia
shipments (the same ratio as for textiles), and were over
(China, Korea, Mongolia, and Vietnam) supplied half of
whelmed by imports. The industry’s trade imbalance has
steadily worsened since 1980. In 1992, the apparel industry’s
the world’s apparel exports in 1991, while the United States
supplied less than 3 percent. At the same time, the Unites
trade deficit was nearly $26 billion, eight times greater than
States received 19.4 percent of world exports, including a
the textile industry’s imbalance, and the worst imbalance of
third of the exports from developing countries.18 (See table
all the manufacturing industries. (See chart 6.)
The apparel industry’s practice of using manufacturing
2 and chart 5.)
workers in Caribbean countries contributed to a portion of
Despite the loss of international market share in the
1970’s, U.S. apparel exports increased in value. During the
increased imports. “Sourcing,” or “807 Sourcing,” as it is
called in the apparel industry, refers to cutting material in
first half of the 1980’s, apparel exports declined as the value
the United States and assembling it in other nations.19 The
of the dollar rose (in 1984, U.S. apparel exports accounted
66 M onthly Labor Review
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Chart 4.
Capital investment by the apparel and textiles Industries in constant dollars, 1965-92
Thousands
Thousands
$4 0 0 0 1------
$4,000
H Apparel
□
Textiles
3,000
3,000
2,000
2,000
1,000
1
1965
1967
1969
1971
1973
I
1975
1977
1979
1981
1983
1985
1987
lili
1989
1,000
1991
Source: U.S. Department of Commerce
product is then imported back to the United States, with du
ties paid only on the value added, and shipped by the U.S.
manufacturer for sale.20 Thus, the count of imports includes
the value added by assembly in these sourcing arrangements.
Although this practice began in the late 1960’s, the
amount of shipments allowed to reenter the United States
was limited by quotas. In 1985, under new bilateral agree
ments with the Caribbean Basin countries,21 unlimited ac
cess was negotiated for firms that, in addition to cutting the
material in the United States, also used U.S.-made material.
This new sourcing agreement is termed 807a, a traditional
type of outsourcing. Firms in the United States operate un
der 807 and 807a sourcing methods. As a result of this lift
ing of import quotas, imports from the Caribbean Basin have
grown rapidly. Between 1987 and 1992, imports under the
807 sourcing programs increased by 180 percent, to $3.8
billion in 1992. Nevertheless, this was still just 14 percent of
total U.S. apparel imports.22
Despite the use of labor that is outside the United States,
determining the precise impact on jobs is impossible. Many
industry leaders— in the American Apparel Manufacturers
Association, the U.S. Department of Commerce, and other
organizations and agencies—believe that, without the prac
tice of 807 sourcing, many U.S. apparel manufacturers
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Federal Reserve Bank of St. Louis
would go out of business, causing a significant loss of jobs
in the industry. Because of this arrangement, domestic manu
facturers have been able to take advantage of the relatively
cheap labor in Mexico and the Caribbean to manufacture
apparel products that are more competitively priced com
pared with East-Asian products. For this reason, 807 sourc
ing may have reduced the demand for imports from Asia,
protecting the employment of domestic workers who con
tribute to some parts of the manufacturing process. As a re
sult, although some apparel assembly jobs in the United
States have moved to the Caribbean Basin or Mexico, even
more might have been lost to East-Asian imports without
this legislation.
Meanwhile, the apparel industry is still confronted by
growing imports. While imports under section 807 are com
prising a larger share of total imports, most imports con
tinue to come from developing Asia (nearly 80 percent in
1990).23 In 1992, apparel imports accounted for 31 percent
of domestic consumption.
Employment outlook and trade agreements
and the Multi-Fiber Arrangement. Among the factors
that are expected to have a substantial impact on employ-
g att
M onthly Labor Review
August 1995
67
Textile, A p p a re l Em ploym ent
Developing and developed countries’ share of
the world export market, in percent, 1965-90
Textiles
D eve lo p in g D e v e lo p e d D eve lo p in g
m a rk e t
m a rk e t
m a rk e t
e c o n o m ie s e c o n o m ie s e c o n o m ie s
Year
1965
1970
1975
1980
1985
1990
.........................
.........................
.........................
.........................
.........................
.........................
N ote:
A p p a re l
16.0
15.4
17.6
22.1
28.0
39.0
76.4
77.6
74.6
69.8
62.2
59.1
14.8
21.1
32.0
36.5
47.9
56.4
D e v e lo p e d
m a rk e t
e c o n o m ie s
69.7
63.5
54.5
51.2
41.5
41.3
Based on sue 65 for textiles and sue 84 for apparel.
S ource:
United Nations
ment in the textiles and apparel industries, perhaps the most
influential will be the trade policy agreed to in the General
Agreement on Tariffs and Trade (GATT). With the support of
the United States, the Multi-Fiber Arrangement will be
phased out over 10 years. This arrangement has been the
textiles and apparel trade agreement in effect among most
nations since 1974, and has been renegotiated and ratified
four times, most recently in 1986.24
The Multi-Fiber Arrangement, a network of bilateral trade
agreements, operates outside the regulations of g a t t , and al
lows countries to place import quotas on textiles and apparel
products that, under g a t t , would not be permitted. The MultiFiber Arrangement permits importing countries to place
quotas on apparel and textile products from selected coun
tries to avoid domestic market disruption. While the arrange
ment has undoubtedly protected some domestic jobs, it was
criticized by consumer groups, several academics, and pro
ponents of free trade because of its cost to consumers and its
protectionist type quotas. A study by William Cline found
that 214,000 jobs were saved in the apparel industry due to
the Multi-Fiber Arrangement, at a cost to consumers of
$46,000 annually per job.25 A separate study by Gary Clyde
Hufbauer, Diane Berliner, and Kimberly Ann Elliott found
that the Multi-Fiber Arrangement had saved 460,000 jobs in
the apparel industry at a consumer cost of $39,000 per job.26
With the phase-out of the Multi-Fiber Arrangement, tex
tile and apparel trade will be conducted under rules and regu
lations of GATT. The phase-out of the Multi-Fiber Arrange
ment will allow increased imports by releasing some prod
ucts from quota limits at set intervals, while the quota limits
on the remaining protected products are raised each year.
These regulations will be set for participating countries and
should allow for freer trade of textile and apparel products
among these countries. As a result of the phase-out, import
restrictions will be eliminated 10 years after it is enacted.27
Several groups have estimated the impact on employment
from the phase-out of the Multi-Fiber Arrangement, but es
68
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August 1995
timates vary dramatically. Estimating effects on employment
is difficult because several important facets of the agreement
have not yet been decided.28 For example, the status of quota
limits for products from China is unknown because that
country is not a member of g a t t .29 Estimating demand for
U.S. products from foreign countries that will have freer
markets also is difficult. In a study published in January
1992, Wharton Economic Forecasting Associates states that
the “direct and indirect impact on the textile and apparel
industries is estimated to be a job loss of 647,000 . . .”.30
A study by the American Textile Manufacturers Institute
estimates that number of jobs will fall by 1.4 million dur
ing the same period, leaving only 300,000 jobs in the indus
tries.31 However, the U.S. International Trade Commis
sion estimated that eliminating all import quotas and tariffs
would reduce employment in the two industries by between
230,000 and 290,000. The Congressional Budget Office
notes that the losses may be even lighter than the trade
commission estimates because the commission’s study did
not take into account the proposal that all industrialized
countries remove their restrictions at the same time; the
continued application of import quotas to countries that are
not members of g a t t , such as Taiwan and China; and that
tariffs on the products may still remain even after quotas are
removed.32
The apparel industry, which is far more labor intensive
and less competitive internationally than the textile indus
try, will probably sustain most of the losses from the new
trade environment. As noted, the textiles industry does not
suffer from severe import competition as does the apparel
industry, but is affected more indirectly: less domestic ap
parel production means fewer domestic textiles are needed.
A possible advantage of the new agreements would be the
opening of markets in developing countries that restrict im
ports of U.S. textile and apparel products. Because the U.S.
textiles industry uses fairly efficient production processes,
demand from foreign apparel producers could increase.
NAFTA. Future employment levels also will be affected by
the North American Free Trade Agreement ( n a f t a ). The
agreement, which took effect January 1,1994, created a freetrade zone among the United States, Canada, and Mexico.
n a f t a is expected to contribute to employment declines in
the apparel industry but may generate job growth in the tex
tiles industry.
With the relatively cheap labor that is available in Mexico,
some apparel manufacturers are likely to move their opera
tions south to be more competitive, n a f t a also may cause
apparel manufacturers to slowly discontinue 807 sourcing
operations in the Caribbean as they reinvest in Mexico, where
finished products would not be subject to duties. A study by
the International Trade Commission concluded that a free
trade agreement would introduce incentives that favor ap
supply that is inadequate for dyeing and finishing yams will
parel investment shifts from Caribbean Basin countries to
impede investments in the near future.34 This will provide
Mexico; but the study could not quantify any effects of this
further stimulus to the U.S. textiles industry. In addition,
shift.33 According to this study, companies that already have
n a f t a will boost production and imports of U.S.-made
invested heavily in the Caribbean may invest in Mexico to * fabrics, according to the Wharton Economic Forecasting
remain competitive, although this would require large capi
Associates.35
tal expenditures.
The impact of n a f t a on imports, exports, and employ
The textiles industry would probably not undergo the same
ment would be expected to occur incrementally over many
shift in its manufacturing base. Because the textiles industry
years. During 1994, the first year after n a f t a took effect, an
is much less labor intensive than the apparel industry, U.S.
nual average employment in textiles was relatively flat for
companies would not have the same incentive to relocate pro
the third consecutive year, and declines in apparel contin
duction. Further, the United States is the largest supplier of
ued. Both developments were in line with expectations for
textile goods to Mexico’s clothing manufacturers and, for
employment trends under n a f t a .
apparel products to remain duty-free throughout the freetrade zone, the apparel products must be made from North
Eastern Europe. The changing political and economic sta
American fiber, spun in North American mills. With an effi
tus of Eastern Europe also may negatively affect employment
cient production process in place, U.S. textiles manufactur
prospects for apparel. With the opening of Eastern European
ers would benefit from increased production in the free-trade
markets, these countries have the ability to become bigger
zone. The U.S. textiles manufacturers are more efficient than
players internationally. Unlike many apparel workers in East
Mexican textile manufacturers, and the elimination of tariffs
Asia, those in Eastern European countries are very skilled.
would make U.S. textile products more attractive to Mexican
This level of skill, coupled with the very low wages, may
apparel producers. Mexican textile manufacturers could, in
allow these countries to produce more expensive apparel prod
the long run, invest in better facilities, but the large capital
ucts, such as tailored suits and coats, at a fraction of the price
outlays required for efficient plants, coupled with a water
paid by U.S. manufacturers. For example, in 1991 the averChart 5.
Imports and exports of apparel products, 1965-91
Percent
Percent
1965
1970
1975
1980
1985
1991
SOURCE: United Nations
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M onthly Labor Review
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69
Textile, A p p a re l Em ploym ent
Chart 6.
Developing countries' share of world exports in apparel products, 1965-92
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
S o u r c e : Department of Com merce
age U.S. apparel worker earned $6.77 an hour; a similarly
skilled worker in the former Soviet Union earned $0.36.36
As incomes rise, however, the appeal of U.S. clothing could
attract buyers in these same countries.
Productivity
Even if the current trade regime were to remain unchanged,
the industries’ employment levels would still be expected to
decline. The Bureau of Labor Statistics estimates that, de
pending on the economy’s growth, the textiles industry will
lose between 85,000 and 160,000 jobs between 1992 and
2005, while losses in the apparel industry will range from
240,000 to 350,OOO.37 Under the current trade regulations,
the Wharton estimate is that the textile and apparel indus
tries, combined, will lose 400,000 jobs during the 19932002 period. This estimate also is based on expected pro
ductivity increases and the domestic industries’ competi
tive disadvantages.
Productivity will continue to have a major impact on em
ployment in the 1990’s. Productivity advances will continue
to build on the uses of computer integrated manufacturing
and quick response. Use of computer integrated manufac
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turing already has begun in the textiles industry. A fully com
puter-integrated spinning mill that virtually eliminates the
need for laborers already has been established in Japan. The
entire process, from placing bales in the opening line to load
ing trucks for shipment, is achieved without human hands
touching the material; maintaining and controlling the entire
plant requires only nine employees.
In the United States, many plants use some form of com
puter integration in manufacturing. For example, a Moun
tain City, t n , automated yarn spinning plant produces 600,000
pounds per week of cotton yarn with fewer than 200 employ
ees. The only handling of material occurs when cotton is un
loaded from trucks and when packed yarn is reloaded for de
livery.38 Computer integrated manufacturing reduces labor
costs and enhances quality and reduces error. Optical scan
ning can detect errors and alert operators immediately.
Fully automated apparel plants are only in the early stages
of development. A fully operational computer integrated man
ufacturing system has the potential to reduce the time needed
to complete a season’s line from 30 weeks to between 5 and 6
weeks.39 Many apparel manufacturers already have started
using computer-aided design systems and modular manufac
turing. These systems have allowed garment manufacturers
to substantially reduce the time needed for design. Modular
manufacturing consists of units or small teams of employees
who produce an entire garment. This team system has in
creased quality and minimized downtime in many plants.40
Dean Vought, president of Textile and Clothing Technol
ogy Corp., an independent research firm, believes that
“advances in manufacturing technology, while needed and
welcome, have a limited impact. . .the wide variety of style
changes and limp fabrics that must be accommodated in
manufacturing make it unlikely that we could reduce direct
labor content by more than 25 percent through all currently
conceivable mechanization and automation.” That still
may not be enough to compete with low wage countries.
Vought emphasized that resources may be better spent “on
developing technology to reduce calendar time rather than
cost Time, service and more accurate response to consumer
demand are where we have an advantage that can be
strengthened through technology.” Thus, computer inte
grated man-ufacturing in the apparel industry may be fo
cused on time-saving techniques. This type of technology
takes the form of improved communications, data manipu
lation, graphics, video imaging, and satellite transmissions
and can be used in product development, marketing and cus
tomer service.41
Quick response manufacturing follows the time-oriented
concept that quicker is better, and is becoming the norm in
the apparel and textiles industry. Quick response programs
use computers to speed the goods, services, and information
in domestic apparel production, tying apparel producers with
textile suppliers and retailers.42 Quick response has become
important in the apparel industry because more retailers are
demanding it as they seek to minimize inventories and markdowns while restocking popular items. For apparel manu
facturers to provide retailers with goods on a quick-turn
around basis, they must be able to receive their manufactur
ing inputs quickly. Therefore, this chain of demand is re
quiring closer partnerships among retailers, apparel manu
facturers, and textile manufacturers.
Quick response helps the U.S. apparel industry to com
pete against foreign manufacturers. Many retailers have little
control over the quality of the products they purchase from
abroad, and many times the quality of the products is not
consistent among shipments. Quick response gives domes
tic manufacturers an advantage because they can deliver bet
ter quality items more quickly. The link between manufac
turers and retailers also provides incentives for producers to
deliver better quality items. One survey of apparel manufac
turers found that 61 percent of respondents had quick re
sponse programs with their retail partners in 1991, up from
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51 percent in 1990, while 32 percent had such programs
with their textile partners, up from 23 percent in 1990.43
All of the above technologies and trends are combining to
enable producers to create better quality products, more
quickly and for less money in both industries. In a time of
rapidly changing economies, and with prospects of freer
trade on the horizon, these practices can enable the textiles
and apparel industry to maintain, or perhaps increase, their
share of the world market.
s u m , employment has declined in the textile and apparel
industries over the past two decades—together they have lost
more than 750,000 jobs. Although the industries are closely
linked, their operations are very different. The textiles in
dustry is concentrated, automated, and efficient. Because the
apparel industry is still very labor intensive, despite new
technologies, it has difficulty competing with foreign pro
ducers in low-wage countries. The apparel industry also is
not as concentrated as the textiles industry. In the United
States in 1987, 21,000 apparel companies shipped goods
valued at $64 billion. The textiles industry had only 5,000
companies producing $63 billion in shipments.44
Between 1949 and 1991, labor productivity in the textiles
industry grew at an average annual rate of 3.9 percent, much
faster than the annual average rate of 2.5 percent for all
manufacturing. Labor productivity in the apparel industry
grew at an annual average rate of only 2.2 percent during
the same time period, slightly slower than the rate for all
manufacturing.
Imports in the textile industry gained about 5 percentage
points of domestic market share from 1970 to 1993, rising
from 4.5 percent to 9 percent. The apparel industry, by con
trast, saw imports rise from about 5 percent to 31 percent
during the same period. Textile production continues to reach
new heights, but apparel production has not returned to its
peak level that occurred in 1987. Industrial production in
the apparel industry is off 6 percent from its July 1987 peak,
according to December 1994 data.
Although the apparel industry continued to lay off work
ers in 1994, employment in textiles was relatively flat. Over
the long term, declines are expected to continue, particu
larly in apparel. Competition will be even fiercer with
stepped up global trade and the lifting of import restrictions.
Labor-saving and time-saving technologies will help domes
tic manufacturers compete against low-wage countries to
maintain (and perhaps expand) domestic and world market
share. Therefore, emerging technologies and opening mar
kets should be the main forces behind the employment trends
in the next 10 years.
□
In
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71
Textile, Apparel E m ploym ent
Footnotes
1Employment data are from the Current Employment Statistics Survey and
appear in Employment, Hours, and Earnings, United States, 1909-1990, Vol
ume II, Bulletin 2370, and Employment, Hours, and Earnings, United States,
1981-93, Bulletin 2429 (Bureau of Labor Statistics, 1991 and August).
2 Production data from Federal Reserve Statistical Release, Industrial Pro
duction and Capacity Utilization, (Federal Reserve System), various issues.
3Productivity data based on unpublished data from the Office o f Productiv
ity and Technology, Bureau o f Labor Statistics, September 1992. Productivity
data for apparel and textiles are available only through 1991.
4 William R. Cline, The Future of World Trade in Textiles and Apparel
(Washington, Institute for International Economics, 1987), table 2.5.
5Centre on Transnational Corporations, Transnational Corporations in the
Man-made Fibre, Textile and Clothing Industries (United Nations, 1987), p.
75.
6 Fariborz Ghadar, William H. Davidson, and Charles S. Feigenoff, U.S.
Industrial Competitiveness, The Case of the Textile and Apparel Industries
(Lexington, m a , Lexington Books, D.C. Heath and Co., 1987), pp. 19-20.
7 Data are “corporate profits before taxes” obtained from U.S. Department
o f Commerce, Bureau o f Economic Analysis, National Income and Products
Accounts, 1959-1988, vol. 2, ( July 1992), table 6.17.
8 Constant-dollar shipments were deflated using the Producer Price Index
for textile and apparel products. The base year is 1982.
9 Some of the larger consolidations were West Point-Pepperell’s acquisition
o f J.P. Stevens and Cluett, Peabody & Co.; the subsequent acquisition o f West
Point-Pepperell by a majority stockholder o f Fruit o f the Loom; the merger of
Spring Industries and M. Lowenstein; and the sale of Cannon Mills to Fieldcrest,
becoming Fieldcrest Cannon. Standard and Poor’s Industry Surveys, Nov.
28, 1991, pp. T76-T77.
10The information on leveraged buy-outs was primarily obtained from Stan
dard and P oor’s Industry Surveys, Nov. 28, 1991, pp. T76-T77.
11 United Nations Centre on Transnational Corporations, Transnational
Corporations in the Man-made Fibre, Textile and Clothing Industries, p. 80.
12 Cline, The Future of World Trade, table 5.5. The high level of import
penetration in the European countries also reflects a higher degree of
intraindustry trade in the European Economic Community.
All international trade statistics are based on Standard Industrial Trade Class
ification codes 65 for textile products and 84 for apparel products, s i t c 65 in
cludes fabricated textile products; SIC 22 does not. s i t c 84 includes only cloth
ing while sic 23 includes clothing and fabricated textile products. Therefore,
sic’s 22 and 23 are not strictly comparable to s i t c ’ s 65 and 84.
13 Exports From Manufacturing Establishments, 1988 and 1989, AR89-1
(Bureau o f the Census, November 1992), p. 30.
14 Bureau o f Labor Statistics, Office o f Employment and Unemployment
Statistics, unpublished data. Data available beginning in 1976.
lsThe labor productivity rates may be overstated because some U.S. apparel
products are shipped to the Caribbean or Mexico for assembly or other work,
and then shipped to the United States where they are included in the U.S.
industry’s total shipments. Therefore, some labor used in manufacturing the
product may not be included in the productivity measures.
16This figure was derived using the annual average aggregate hours from
the Current Employment Statistics Survey and total shipments from the Bu
reau o f the Census.
17 Ghadar and others, U.S. Industrial Competitiveness, pp. 16-17.
18Monthly Bulletin of Statistics, vol. XXXV, no. 5, special table D, and vol.
XI, no. 2, special table C and various other issues including special tables C
and D. (New York, United Nations, Department of Economic and Social De
velopment, Statistical Division, May 1981). The makeup of countries included
in the developing economies has changed as centrally planned economies, such
as Eastern European countries, shift to open markets.
19 “The term 807 refers to a tariff paragraph in Schedule 8 o f the U.S. Tariff
Code that defines the covered articles as follows: ‘Articles assembled abroad in
whole or in part o f fabricated components, the product o f the United States,
which a) were exported in condition ready for assembly without further fabri
cation, b) have not lost their physical identity in such articles by change in
form, shape or otherwise, and c) have not been advanced in value or improved
in condition abroad except by being assembled and except by operations inci
dental to the assembly process such as cleaning, lubricating, and painting.’”
See U.S. Apparel Imports Under807 (Arlington, v a , American Apparel Manu-
72
M onthly Labor Review
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Federal Reserve Bank of St. Louis
August 1995
facturers Association, undated), p. 1.
20Although most o f tariff code 807 imports are from the Caribbean Basin,
the same agreement is in effect with Mexico and is called Special Regime. These
imports from Mexico still enter the United States under tariff code 807 and any
reference here to 807 imports includes imports from the Caribbean and Mexico.
21 Belize, Costa Rica, the Dominican Republic, El Salvador, Guatemala,
Haiti, Honduras, and Jamaica are the primary countries in the Caribbean Basin
initiative.
22 “U.S. 807 Apparel Imports,” Table 1.
23 Monthly Bulletin of Statistics, vol. XLV1I, no. 5 (New York, United Na
tions, Department of Economic and Social Development, Statisticals Division),
special table D .
24 Four multi-fiber arrangements were negotiated between 1973 and 1986
(MFAI - MFAIV). The Multi-Fiber Arrangement was not negotiated and rati
fied again upon its expiration in 1991 because most countries had agreed that it
would be eliminated. But until negotiations for elimination of the arrangement
were completed, MFA IV was extended.
25 Cline, The Future of World Trade, p. 193.
26Gary Clyde Hufbauer, Diane Berliner, and Kimberly Ann Elliott, Trade
Protection in the United States: 31 Case Studies (Washington, Institute for
International Economics, 1986), p. 148.
27The information on the schedule o f the Multi-Fiber Arrangement phase
out was obtained from “Multilateral Trade Negotiations, The Uruguay Round,”
UR-91-0185 (New York, Trade Negotiations Committee, General Agreement
on Tariffs and Trade Secretariat, December 20,1991).
28Three studies from the Wharton Economic Forecasting Association, Ameri
can Textile Manufacturers Institute, and U.S. International Trade Commission
assume that import quotas will be lifted from all countries.
29According to the Executive Summary, Results of the gait Uruguay Round
of Multilateral Trade Negotiations “China will not be permitted to sign the
agreement on textiles and clothing until it becomes a member of g a t t , and, until
then, will not be the beneficiary of any quota liberalization by the United States.”
30 “The Impact o f Eliminating the Multi-Fiber Arrangement on the U.S.
Economy, Isolating the Textile and Apparel Components of g a t t ” (Philadel
phia, the w e f a Group, 1992).
31 Carlos Moore, “Phasing Out the Multi-Fiber Arrangement in the Uruguay
Round: The Impact on U.S. and Foreign Producers” (Washington, D C , Ameri
can Textile Manufacturers Institute, March 1991).
32“Trade Restraints and the Competitive Status o f the Textile, Apparel, and
Nonrubber Footwear Industries” (Congressional Budget Office, 1991).
33“Potential Effects of a North American Free Trade Agreement on Apparel
Investment incBERA Countries” Report to the U.S. Trade Representative (Wash
ington, United States International Trade Commission, July 1992) p. 72.
34 “Potential Impact on the U.S. Economy and Selected Industries o f the
North American Free-Trade Agreement,” Publication 2596 (Washington, U.S.
International Trade Commission, January, 1993) p. 8-3.
35 “A brighter day is dawning for U.S. textiles in 1993,” Textile World, Janu
ary 1993, p. 40.
36The hourly wage figure for workers in the former Soviet Union was ob
tained from “Labor costs - From Pakistan to Portugal,” Bobbin Magazine,
September 1992, pp. 116-119.
37 James C. Franklin, “Industry output and employment,” Monthly Labor
Review, November 1993, p. 54, table 50.
38 “Mountain City: Oh, What a M ill!” Textile World, June 1991, p. 50.
39 “The Impact of Technology on Apparel, Part 1,” 1991 Report of the Tech
nical Advisory Committee, American Apparel Manufacturers Association,
p. 12.
40 Industry Trade and Technology Review (Washington, U.S. International
Trade Commission, October, 1992), p. 9.
41 “Time is of the Essence at [TC]2,” Bobbin Magazine, May 1992, p. 24.
42 Industry Trade and Technology Review (Washington, U.S. International
Trade Commission, October, 1992), p. 9.
43 Ibid., p. 9.
441987 Census of Manufacturers: Concentration Ratios in Manufactur
ing. MC87-S-6 (Bureau of the Census, February 1992), table 5.
Rubber Workers ends strike
The United Rubber Workers ended its
10-month strike against Bridgestone/
F irestone, Inc.— the longest work
stoppage ever in the rubber industry—
following the return to work of 700
members of Local 713 in Decatur, i l .
The union accepted the terms of the
tiremaker’s “final offer,” which had
triggered the international’s walkout at
five of the company’s plants last July,
idling some 4,200 workers. After the
walkout, Bridgestone/Firestone uni
laterally imposed terms of its final
offer, which included cuts in wages,
health insurance, and pension benefits,
and changes in work rules. In addition,
the company hired some 2,300 workers
to permanently replace strikers.
According to one union insider, the
agreement to return to work was not a
capitulation on the part of the union,
but a strategic attempt to forestall a
union decertification election, keep the
company from hiring more replacement
workers, and stop union members from
crossing picket lines at the plants. Ac
cording to the press, the union also was
worried about its members, who had
been without paychecks for 10 months.
A Bridgestone/Firestone spokesper
son said the company was glad to re
ceive the union’s offer to uncondition
ally return to work. He said the com
pany would evaluate workload and
staffing requirements before informing
the union of the number of employees
who would be needed. Press reports
subsequently indicated that the com
pany would recall 153 strikers.
Under terms of the imposed agree
ment, hourly wages for most job classi
fications are slashed $5.34, to around
$12. Pay for new hires is cut 30 per
cent, and incentive rates are reduced.
“ Industrial Relations” is prepared by
Michael H. Cimini and Charles J.
Muhl of the Division of D evelop
ments In Labor-Management Rela
tions, Bureau of Labor Statistics, and
is largely based on information from
secondary sources.
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Pension benefits are frozen at their ex
isting levels. The work schedule is
amended to allow for continuous opera
tions with 12-hour shifts—that is, 12
hours on, followed by 12 hours off.
Following its failed strike against
B ridgestone/Firestone, the Rubber
Workers ( u r w ) approved a merger with
the United Steelworkers of America
( u s a ). In a joint statement, union lead
ers said the merger will “combine our
strength and resources in the political
and legislative arenas, at the bargain
ing table, and.. .will open the door wide
for aggressive organizing among work
ers wanting to join a growing force in
democratic unionism.”
Both unions have suffered declining
membership in recent years. The cur
rent URW membership of 98,000 is
down from a peak of 180,000 in 1980,
while USA membership has steadily
fallen from more than 1 million in 1980
to its current level of 565,000. The
merger will result in a combined union
of approximately 665,000 members.
The merger gives u r w members ac
cess to the USA strike fund, currently at
$162 million. The financial support is
im portant because the walkout at
Bridgestone/Firestone depleted the
URW’s strike fund in December 1994.
The union was forced to borrow $3 mil
lion and raise membership dues to con
tinue paying strike benefits. The timing
of the merger is also fortuitous for the
u r w because the union faces a heavy bar
gaining schedule in 1995-96, when it
renegotiates 232 contracts.
Cost saving plans
re ac h e d at usAir
On the heels of a similar settlement
with the Air Line Pilots Association,
usAir Group signed a 5-year tentative
agreement with the International Asso
ciation of Machinists (IAM ) — moving
the financially strapped carrier closer
to its goal of reducing total labor costs
by $2.5 billion over the next 5 years.
The airline reportedly has pledged to
slash an additional $2.5 billion in oper
ating costs over the same period by elimi
nating routes, selling old aircraft, and
instituting other cost savings as part of a
broader financial rescue package de
signed to ensure the carrier’s survival.
Like the Pilots’ agreement, the i a m pact
is contingent on approval of usA ir’s
board of directors and stockholders, as
well as the signing of agreements with
all the carrier’s unions.
Negotiators for usAir and the i a m
agreed to cut wages and introduce rule
changes that are intended to provide
“substantial” cost savings to the carrier
in exchange for improved job security,
a greater say in how the company is run,
and certain financial returns. The ac
cord covered some 14,500 i a m mem
bers, including 8,000 mechanics and
related employees and 6,500 fleet ser
vice employees, for whom this will be
their first agreement.
The major terms of the cost saving
plan call for i a m members to take a
12.9-percent pay cut in exchange for
20 percent of usA ir’s common stock
and $400 million in preferred stock to
be distributed among all employees, 4
em ployee-selected members on the
company’s new 12-member board of
directors, and a profit-sharing plan.
The accord also enhances job security
by including a no-layoff clause for the
duration of the agreement, banning the
transfer of work to foreign-based main
tenance facilities, granting preferential
hiring at commuter carriers that are
part of the usAir system, and provid
ing job protection in event of an asset
sale or merger. Other terms allow for
4-day, 10-hour-a-day workweeks; and
increase pension benefits by $15,000
for employees aged 58 or older.
The Association of Flight Atten
d ee s tentatively signed a pact similar
to the one reached by the i a m , but it
was rejected by the rank and file. The
carrier has yet to negotiate an agree
ment with its remaining union, the
Transport Workers, which represents
about 270 employees.
M onthly Labor Review
August 1995
73
Industrial Relations
Early settlem ent
a t Bell Atlantic
More than 3 months before their con
tract was set to expire, Bell Atlantic
Corp. and Locals 827 and 1944 of the
International Brotherhood of Electrical
Workers reached agreement on a 5-year
contract covering some 9,500 employ
ees, most of whom work in New Jersey
and Pennsylvania. Bell Atlantic hopes
that the settlement will serve as a pat
tern for its other major bargaining unit,
37,000 employees represented by the
Communications Workers of America.
According to Bell Atlantic’s chief ne
gotiator, A1 Koeppe, “This is a progres
sive contract that fairly balances the
needs of Bell Atlantic in a competitive
marketplace with the needs of employ
ees and the i b e w for job security. It em
bodies the spirit of respect, trust, and
teamwork between the company and the
i b e w —and our resolve to work coopera
tively to meet competitive threats.”
The accord calls for a $1,000 rati
fication bonus, plus wage increases of
3 percent in the first year of the con
tract, 2.75 percent in both the second
and third years, and 3 percent in each
of the final 2 years. The first $300 of
the first-year wage increase will be
paid as a lump sum.
The settlem ent includes several
changes in benefits and work rules. It
improves the profit-sharing plan and
increases pension benefits. The contract
requires employees who retired after
1989 to contribute 2 percent of their an
nual pension benefits to a trust fund to
help pay for health insurance premiums
beginning in 1997, with the rate in
creasing to a maximum of 10 percent
after the year 2000. The pact establishes
two pilot programs, a 9-month test pro
gram of 4-day workweeks for construc
tion workers and a 1-month test of
telecommuting (working at home using
computers and other electronic equip
ment) by clerical workers. Under the
telecommuting program, the company
will provide all necessary equipment.
Digitized for74
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August 1995
Other terms add coverage of preventive
care services to health benefits; provide
$750 awards to employees who com
plete training programs “which en
hance competitive technology and cus
tomer service skills in telecommunica
tions”; and strengthen job security pro
visions by providing protection against
layoffs for many bargaining unit em
ployees and guaranteeing “virtually all”
feeder and distribution facilities work
on Bell Atlantic’s new broadband net
work to bargaining unit employees.
Twin Cities nurses
reach a c c o rd
Using interest-based bargaining that
emphasized the exchange of issues
important to each side, the Minnesota
Nurses Association and the M etro
politan Healthcare Council settled on
a 3-year pact that clarifies the role of
registered nurses in the health care
delivery process. The agreem ent,
which also provides wage increases,
im proves advanced education ben
efits, and addresses workplace vio
lence, covers some 7,000 nurses at 12
M inneapolis-St. Paul area hospitals
represented by the council. Using the
“win-win” bargaining approach, the
parties were able to reach agreement
2 weeks prior to the expiration of the
previous contract, in stark contrast to
past contentious negotiations that in
cluded a 39-day strike in 1984. The
parties recognized “a mutual interest
in developing health care delivery
systems which will provide quality
care on a cost efficient basis [and]
recognize the accountability of the
registered nurse.”
Like other health care providers
nationwide, the Twin Cities hospitals
faced declining revenues and increas
ing expenses in recent years. Fearing
that local hospitals might follow the
industry pattern of replacing higherpaid re g istered nurses w ith u n li
censed technical or assistant person
nel to reduce labor costs, the union
sought to include protective measures
to ease the transition following a
change in work force composition.
The accord addresses a number of
w o rk p lace issu es, in clu d in g the
nurses’ role in providing health care
to patients. Contract language guar
antees that only nurses will “assess,
plan, and evaluate patient or client
nursing care needs.” The pact estab
lishes a labor-management committee
to address any proposed changes in
health care delivery systems and to
determine the exact role of nurses and
unlicensed assistants in delivering
care. Nurses are perm itted “to del
egate those aspects of nursing care the
nurse determines appropriate based
on her or his assessment.” Each hos
pital must provide a system of patient
classification based on demonstrated
patient needs and appropriate nursing
interventions that will be used to de
termine nursing staff levels. Any po
tential changes to patient care deliv
ery systems must be discussed jointly
by the committee and the hospitals.
The hospitals agreed to provide
cross-training to prepare nurses for in
dustry changes that may result in the
use o f more unlicensed assistants.
Nurses are eligible for up to $300 per
year for training to prepare them for a
second clinical service, for national cer
tification in their area of practice, or for
complementary therapies that may en
hance their skills. Nurses pursuing an
advanced degree also are eligible for
annual tuition reimbursement of $2,000
(was $1,500) and may work flexible
schedules to attend classes.
The pact requires the hospitals to
notify nurses of an impending layoff,
and to offer voluntary leaves of ab
sence to all nurses before reducing
nursing care hours. Nurses adversely
affected by a reduction in nursing care
hours have the option to transfer to
other vacant positions for which they
are qualified, to replace less senior
nurses within their clinical group or
in other clinical groups, or to accept
layoff and retain full recall rights. In the
event of a layoff or major restructuring,
full-time senior nurses aged 58 or older
with 20 years of service have the option
to choose early retirement with complete
health insurance until age 65.
To protect bargaining unit positions,
hospitals are required to give advance
notice of any promotion or transfer of
an employee out of the bargaining unit.
Furthermore, hospitals must provide
written notice of the establishment of
any new nonexecutive position and their
initial determination as to whether the
position will be included in the bargain
ing unit— which the union may contest.
The union also must be notified of any
new programs or business ventures, in
cluding any possible effect on the num
ber of positions in the bargaining unit.
Nurses will receive wage increases of
3 percent in the first and second contract
years, and 2.6 percent in the third year.
The starting salary for nurses ranges from
$2,774 to $2,872 per month, depending
on educational level. Nurses with 20 or
more years of experience earn between
$4,161 and $4,263 per month. Effective
June 1, 1997, each nurse certified in a
specialty area will receive an annual bo
nus of $360.
Citing a commitment to provide a
workplace free of hostile, abusive, and
disrespectful behavior, the parties agreed
to form “response teams” to address all
emergency situations in which physical
violence, the threat of physical violence,
or verbal abuse occurs. Participating
hospitals will educate employees on
methods of preventing workplace
violence. In addition, nonemergency
incidents will be recorded, reported, and
evaluated by the nursing Health and
Safety Committee when a registered
nurse is involved.
Other terms of the contract grant 3
additional days of leave for nurses with
15 to 19 years of service and 5 addi
tional days for those with 20 or more
years of service for professional deve
lopment, continuing education, or per
sonal renewal; provide a $100 monthly
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supplement to nurses with master’s de
grees beginning in 1996; and increase
the maximum monthly long-term dis
ability payment to 65 (was 60) percent
of monthly compensation, to a maxi
mum of $5,000, while lowering the
work requirement for long-term disabil
ity insurance eligibility from 64 to 48
hours every 2 weeks.
LA cleanin g service p a c t
As part of its “Justice for Janitors” drive
to organize and bargain for commercial
cleaning service workers, Local 339 of
the Service Employees International
Union ( s e i u ) negotiated separate but
parallel 5-year contracts covering some
8,500 janitors working for 21 cleaning
companies in the Los Angeles, CA, area.
The pacts bring workers under one uni
fied wage and benefit system, while
maintaining health and pension benefits
and strengthening job protection. The
two largest employers participating in
the coordinated bargaining were Inter
national Service Systems, Inc. and
American Building Maintenance, each
with about 3,000 employees.
The settlement will replace the 4tiered wage and benefit structure with
one that provides the same wage and
benefit levels to all employees. Under
the prior contract, tier 1 employees
received a starting rate of $6.80 per
hour and full family health care cov
erage paid for by the employers; tier
2 employees received $5.40 per hour
and full individual health care cover
age; and tier 3 workers received $4.70
per hour and no benefits except for
paid vacations. The union was recog
nized as the bargaining agent for tier 4
workers, but did not negotiate economic
benefits for them. Tier 1 employees will
receive a wage increase of $1 per hour
over the contract term, while employ
ees in tiers 2-4 will be brought up to the
existing wage and benefit levels speci
fied for tier 1 workers over the next 5
years.
Language changes in the contract im
prove job security and selection provi
sions. Employers must now cite specific
reasons, such as a building vacancy or a
change in cleaning specifications, before
implementing a work force reduction.
Previously, the employers could lay off
employees based solely on their own or
their clients’ needs. Terms also stipulate
that the selection of employees for vacan
cies will be determined by seniority as
long as selected applicants can perform
the job in question. Seniority had previ
ously been the determining factor only
when merit and ability were judged equal.
Other terms of the pact include a
maintenance of benefits provision for
health care, under which employers pay
all premium costs and cover prescrip
tion drugs and vision care; and a con
tinued employer contribution of 10 cents
per hour to the pension fund for tier 1
employees.
The new agreement is the culmina
tion of an 8-year organizing campaign
by the union to represent workers of
commercial cleaning firms in the Los
Angeles area. The union has increased
its representation in the industry from
about 1,500 workers in 1987 to 8,500
in 1995, about 70 percent of the area’s
cleaning service employees.
A laska Airlines p a c t
ends long stalem ate
After more than 3-1/2 years of contract
talks, negotiators for Alaska Airlines
and the International Association of
Machinists ( i a m ) reached agreement on
a 4-year contract covering 2,200 cleri
cal, office, and passenger service work
ers employed in a variety of locations
served by the airline, including Anchor
age and Juneau, a k ; Portland, o r ; L os
Angeles and San Francisco, CA; Phoe
nix, a z ; and Seattle, WA. The settlement
came just 4 days after the National Me
diation Board—the Federal Agency that
administers labor law in the industry—
declared a “30-day cooling-off’ period
following the parties’ refusal to resolve
their dispute through arbitration. Wage
M onthly Labor Review
August 1995
75
Industrial Relations
increases and benefits were the major
sticking points in negotiations.
Alaska Airlines sought a 5-year wage
freeze, elimination of the cost-of-living
adjustment (CO LA) provision, and in
creased employee copayments towards
health insurance premiums, while the
union opposed these proposals. The
eventual settlement between the carrier
and i a m allows Alaska airlines to hold
operating costs in check and preserves
employees’ health care coverage.
The contract calls for seniority-based
bonuses ranging between $750 and
$1,500 in each of the first 3 contract
years. In the fourth year, employees will
receive a general wage increase of 3
percent. The settlement eliminates the
parties’ c o l a clause.
Other changes increase the maxi
mum annual accrual of compensatory
time from 40 to 120 hours; permit train
ing to be counted as time worked for
overtime calculation; and continue the
employee option to use a health mainte
nance organization or preferred-pro
vider organization, while adding dental
and vision coverage. The parties also
agreed to an “early reopener” in May
1999, which requires them to seek me
diatory assistance from the National
Mediation Board if a settlement is not
reached within 6 months.
Like many carriers in the industry,
Alaska Airlines was in a financially pre
carious position in the late 1980’s be
cause of revenue decreases that had re
sulted from fare wars and cut-throat
competition in its short-haul Northwest
markets, and because of high operating
costs, in part from labor contracts.
When current chairman and CEO Ray
Vecci took control in 1991, the airline
undertook severe cost-cutting measures
that included canceling construction of
two new maintenance bases, deferring
planned aircraft purchases worth $2 bil
lion, renegotiating aircraft leases, dis
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August 1995
continuing flights in unprofitable mar
kets, and even cutting back on the in
flight meals that had contributed to the
carrier’s high customer service ratings.
Furthermore, Alaska Airlines attempt
ed to negotiate cost cuts and constraints
in its labor contracts, producing strained
relations and protracted negotiations with
pilots, flight attendants, and other service
workers. The carrier reached cost-cutting
agreements that included flexibility in
pay and scheduling with iAM-represented
ground service workers in November
1992, after 4 years of negotiations (see
Monthly Labor Review, Feb. 1993, p. 65);
the pilots in January 1993; and flight
attendants in February 1994, after 3-1/2
years of negotiations and a number of
short, sporadic work stoppages (see
Monthly Labor Review, June 1994). In
spite of the sometimes tense negotiations
between the parties, airline and union
leaders have indicated that their
relationship has improved because they
have recognized the need for collective
effort in meeting the challenges presented
in their markets.
As a result of Alaska Airlines’ cost
cutting initiatives, its financial viability
has recently improved, despite the en
try of Southwest Airlines and the United
Shuttle into its market. During the first
9 months of 1994, the carrier reported a
profit of $27.6 million on $997.7 mil
lion in gross revenue, compared with a
$10.6 million loss on $851.1 million in
revenue during the same period in 1993.
The carrier’s cost per seat mile declined
from 10.2 cents in 1992 to 9.9 cents in
1993, and to 8.6 cents in 1994.
Settlem ent a t Rockwell
International
Members of Local 1362 of the Interna
tional Brotherhood of Electrical Work
ers approved a tentative 3-year contract
covering some 2,000 production and
maintenance workers at Rockwell Inter
national Corp.’s Collins Division facil
ity in Cedar Rapids, i a .
The settlement calls for an immedi
ate $600 lump-sum payment, a 50-cent
hourly wage increase in the first year of
the contract, an $1,800 lump-sum pay
ment in the second year, and a 3-per
cent wage increase in the third year. It
continues the existing cost-of-living ad
justm ent provision, which provides
quarterly payments equal to 1 cent an
hour for each 0.3-point increase in the
Consumer Price Index for Urban Wage
Earners and Clerical W orkers— but
adds a trigger in each year. The index
must rise 4 percent in the first year and
3 percent in the last 2 years before
c o l a ’s are paid.
The pact introduces several changes
in benefits. It sets employee contribu
tions towards medical insurance premi
ums at $4 per month (was $14) for
single coverage, $7 per month (new) for
2-party coverage, and $11.50 per month
(new) for family coverage. The contract
levies a $35-per-m onth penalty for
spouses of employees enrolled in a
Rockwell health care plan who refuse
coverage under their own employers’
health care plans. The accord cuts the
amount of time laid-off employees can
continue medical coverage at their own
expense, from 24 to 18 months immedi
ately and to 12 months effective May 1,
1996. The settlement obligates Rockwell
to match the first 1 percent of salary that
an employee invests in the 401(k) thrift
savings plan, up to $250 per year.
Other terms create an employee skill
development program designed to pro
vide employees with skills they will
need in the future; enhance recall rights;
and require the company to discuss sub
contracting of work that can not be done
by bargaining unit employees for “com
petitive reasons.”
□
M aking school p a y
Why Our Kids D on ’t Study: An
Economist’s Perspective. John D.
Owen. Baltimore, m d , The Johns
Hopkins University Press, 1995,
136 pp„ $29.95.
High school graduates in the United
States are academically among the most
poorly prepared in the world. John D.
Owen, in Why Our Kids Don’t Study:
An Economist’s Perspective, suggests
that this situation can be explained as
an economic phenomenon. Students
are economic beings and, in their scho
lastic behavior, respond to incentives,
or the lack of them.
Owen, an economist at Wayne State
University in Detroit, uses the tools of
labor economics to analyze shortfalls in
student achievement. He has tried to
reach beyond economists and other so
cial scientists by avoiding mathematical
analysis, graphs and charts, and fully
explaining technical terms. The result is
a highly readable book that will appeal
to anyone concerned with problems in
education in the United States.
Owen briefly reviews the prevailing
theories about why students do not
study. Among the culprits are excessive
exposure to television and popular mu
sic; the notion that study is a challenge
to youth self-esteem; and that adults
place little value on studying and
achievement. Although these factors
may play a part in low academic achieve
ment, the real explanation is that study
ing does not pay, Owen writes. In other
words, students do not see economic
returns from their academic effort. Stu
dents generally may stay in high school
with little effort, and upon graduation,
find their academic record counts for
very little in obtaining a job. In addi
tion, colleges, particularly those that are
not among the elite, may accept stu
dents more on their ability to pay than
on their academic record. As a result,
the labor market does not adequately
reward study and does not provide
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Federal Reserve Bank of St. Louis
needed incentives to achieve in school.
Moreover, bias against academic
achievement is a problem in the public
school system, Owen writes. Institutions
receive financial incentives for large en
rollments, regardless of the quality of stu
dents, and may even receive additional
funds when achievement drops. He also
cites studies that imply a societal bias
against education for its own sake when
education promotes appreciation of sub
jects such as art and literature, or what is
termed “culture.”
Owen proposes to change the incen
tives for students, teachers, and schools.
Students would work harder if schools
and employers improved the exchange
of student academic information and
employers used this information in hir
ing decisions. He includes a role for
Federal Government policies that could
foster integration of school and work in
work-study programs.
National or regional examinations
might encourage students, teachers,
and schools to work harder if employ
ers used the results of these exams in
hiring decisions. Policies to encourage
school choice would force schools to
com pete for students and students
would compete for school admissions.
Not everyone will agree with Owen’s
analysis of the problem or with his pro
posals, but few would dispute the need
for a better educated work force to raise
U.S. productivity and allow corporations
to better compete in world markets. The
findings and proposals in John Owen’s
book are valuable additions to the debate
about educational reform.
—Pat Nielsen
Bureau of Labor Statistics
A tlan ta region
Labor rights overseas
Trade and Labor Standards: A Review
of the Issues. Gary Fields, ed. Paris,
o e c d , 1995, $14, 35 pp.
The decision last year by officials of
the Organization for Economic Coop-
eration and Development to study trade
and labor standards represented a break
from the past. In April, the o e c d ,
through the efforts of its two director
ates covering trade and employment
and labor issues, released the first prod
uct, Trade and Labor Standards: A Re
view of the Issues, edited by economist
Gary Fields. The book aims to review
the main issues of the debate on
whether and how to promote labor
rights internationally.
The book’s strongest feature is its
analytical framework. It contends that
certain labor regulations may reflect
“basic human rights in the workplace”
to be honored in poor and rich coun
tries alike. These include:
• a prohibition on slavery;
• a responsibility to provide informa
tion about unhealthy working con
ditions;
• the right of children to not work;
long hours whenever family circum
stances allow; and
• freedom of association.
Fields suggests that governments
seek international agreements on these
rights. But he does not explain why the
current International Labor Organiza
tion Conventions on these issues are in
adequate.
Beyond these four rights, the book
suggests that setting labor standards be
left to individual countries. He criti
cizes more ambitious efforts to coordi
nate labor standards for being intrusive,
patronizing, or protectionist. The book
also faults national laws banning the
import of prison-made goods despite in
ternational trade rules that permit such
bans. Fields says that if prison inmates
are forced to work, their output should
be marketed in domestic and foreign
markets.
Another issue the book covers is
whether legislation can “push up,” or
improve labor conditions. The author
suggests that labor markets do not suf
fer “market failure,” and that, as a re
sult, government’s role should be mini-
M onthly Labor Review
A ugust 1995
77
Book Reviews
mal. Yet little is said about the inability
of employers to tailor labor standards
to each employee. Moreover, the book
does not discuss noneconomic ration
ales for government intervention. This
is an odd omission in a book about la
bor standards, considering the longtime
international cooperation in advancing
worker rights.
Fields suggests that the “pull” of eco
nomic development on labor conditions
can be powerful. Relying on several
studies, he concludes that higher na
tional income translates into greater re
turns to labor. He also cites evidence
from Asian economies demonstrating
that “labour earnings do not have to be
suppressed in order for outward-ori
ented economic growth to be rapid.”
Fields also points to some negative
im plications. G iving “prim acy to
labour standards, if premature, can pre
clude com petitiveness in trade,” he
says. Unfortunately, he does not cite
specific examples to back this claim.
The reader is left to wonder if these
cases involve adherence to interna
tional labor conventions, or episodes in
which governments have taken actions
not required by ilo conventions, such as
raising wages.
The greatest disappointment in the
book is its failure to review many key
issues. For example, do high labor stan
dards contribute to human development
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and economic growth? What have been
the economic effects in episodes where
governments retreated on legislated
worker rights? Does a higher g d p per
capita increase the chances that a gov
ernment will ratify il o conventions?
How much international trade is pro
duced in conditions that seriously vio
late core il o Conventions?
In 1964, when the Johnson Adminis
tration first considered seeking oecd in
volvement in matters related to trade
and labor standards, an internal Federal
Government memorandum cautioned
that “ oecd consideration of a matter of
this kind is likely to be very slow mov
ing.” More than 30 years later, this pre
diction remains on the mark. For a first
effort, this new o e c d publication is a
useful addition to the literature. But as
the o ecd continues its work program on
this topic, I hope that future studies will
offer more in-depth analysis.
Steve Chamovitz
Com petitiveness Policy Council
W ashington, DC
State of the union
The State of Working America, 19941995. By Lawrence Mishel and
Jared Bernstein. Armonk, n y , M. E.
Sharpe, 1994, 410 pp., $55, cloth,
$24.95, paper.
August 1995
Every 2 years the Economic Policy In
stitute releases its latest findings on the
country’s economic health, with empha
sis on changes affecting working men
and women. In this volume, fourth in
the series, the authors present a broad
variety of published and unpublished
data about employment, unemployment,
wages, hours, family incomes, taxes,
wealth, and poverty in well-crafted
prose, and illustrated in 225 tables and
77 charts.
All told, their diagnosis is “one of
great disparities” in income and wealth,
caused partly by market disadvantages
that hinder three-fourths of the work
force who do not have a college degree.
Their docum entation of disturbing
trends in wages and benefits is particu
larly comprehensive; much of it is based
on their own original analysis of de
tailed data.
In their view, the forces behind those
trends— shrinking manufacturing jobs,
dwindling unionization, a falling mini
mum wage, defense downsizing, and
expansion of international trade—hold
out no prospect for an early decline in
inequality. The fifth volume in this se
ries, due in December 1996, will reex
amine that prognosis.
—Robert A. Senser
Reston, va
Current Labor Statistics
Notes on Labor Statistics.................... so
Comparative indicators
1. Labor market indicators........................................................
2. Annual and quarterly percent changes in
compensation, prices, and productivity..........................
3. Alternative measures of wages and
compensation changes.......................................................
90
91
91
Labor force data
4. Employment status o f the population,
seasonally adjusted.............................................................
5. Selected employment indicators,
seasonally adjusted.............................................................
6. Selected unemployment indicators,
seasonally adjusted.............................................................
7. Duration o f 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 o f 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.............................................................
93
94
94
95
95
96
96
97
99
99
16. Average weekly earnings by industry................................ 101
17. Diffusion indexes of employment change,
seasonally adjusted............................................................. 102
18. Annual data: Employment status of the population........ 102
19. Annual data: Employment levels by industry..................... 103
20. Annual data: Average hours
and earnings levels by industry....................................... 103
Labor compensation and collective
bargaining data
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Federal Reserve Bank of St. Louis
27. Average specified compensation and wage rate
changes, bargaining agreements covering
1,000 workers or more.......................................................
28. Specified changes in cost o f compensation in
private industry settlements covering 5,000
workers or more..................................................................
29. Specified compensation and wage adjustments,
State and local government bargaining situations
covering 1,000 workers or more......................................
30. Work stoppages involving 1,000 workers or more...........
111
112
113
113
92
15. A verage hourly earnings b y in d u s tr y ...................................... 100
21. Employment Cost Index, compensation,
by occupation and industry grou p ...................................
22. Employment Cost Index, wages and salaries,
by occupation and industry grou p ...................................
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 s iz e ...................
25. Participants in employer-provided benefit p la n s............
26. Specified compensation and wage rate changes
from contract settlements, and effective wage
rate changes, agreements covering 1,000
workers or m ore................................................. ................
Labor compensation and collective
bargaining data—Continued
104
106
107
108
109
Price data
31. Consumer Price Index: U.S. city average, by expenditure
category and commodity and service groups................. 114
32. Consumer Price Index: U.S. city average and
local data, all ite m s............................................................ 117
33. Annual data: Consumer Price Index, all items
and major groups................................................................ 118
34. Producer Price Indexes by stage of processing................. 119
35. Producer Price Indexes for the net output o f major
industry groups..................................................
120
36. Annual data: Producer Price Indexes
by stage of processing........................................................ 120
37. U.S. export price indexes by Standard International
Trade Classification........................................................... 121
38. U.S. import price indexes by Standard International
Trade Classification............................................................ 122
39. U.S. export price indexes by end-use category................. 123
40. U.S. import price indexes by end-use category................ 123
41. U.S.international price indexes for selected
categories o f services......................................................... 124
Productivity data
42. Indexes o f productivity, hourly compensation,
and unit costs, data seasonally adjusted........................
43. Annual indexes of multifactor productivity.......................
44. Annual indexes of productivity, hourly compensation,
unit costs, and prices.........................................................
45. Annual indexes o f output per hour for selected
industries.............................................................................
124
125
125
126
International comparisons data
46. Unemployment rates in nine countries,
data seasonally adjusted.................................................... 128
47. Annual data: Employment status o f the civilian
working-age population, 10 countries........................... 129
48. Annual indexes of productivity and related measures,
12 countries......................................................................... 130
Injury and Illness data
HO
49. Annual data: Occupational injury and illness
incidence rates.................................................................... 131
M onthly Labor Review
August 1995
79
Notes on Current Labor Statistics
This section of the Review presents the prin
cipal statistical series collected and calcu
lated by the Bureau o f Labor Statistics:
series on labor force; employment; unem
ployment; labor compensation; collective
bargaining settlements; consumer, producer,
and international prices; productivity; inter
national 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 in
formation are cited.
General notes
The following notes apply to several tables
in this section:
Seasonal adjustment. Certain monthly
and quarterly data are adjusted to eliminate
the effect on the data of such factors as cli
matic conditions, industry production sched
ules, opening and closing of schools, holi
day 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 o f past experi
ence. When new seasonal factors are com
puted each year, revisions may affect sea
sonally adjusted data for several preceding
years.
Seasonally adjusted data appear in tables
1-14, 16-17, 42, and 46. Seasonally ad
justed labor force data for 1994 in tables 1
and 4 -9 were revised in the February 1995
issue of the Review. Seasonally adjusted es
tablishment survey data shown in tables 1214 and 16-17 were revised in the July 1995
Review and reflect the experience through
March 1995. A brief explanation o f the sea
sonal adjustment methodology appears in
“Notes on the data.”
Revisions in the productivity data in
table 42 are usually introduced in the Sep
tember issue. Seasonally adjusted indexes
and percent changes from month-to-month
and quarter-to-quarter are published for nu
merous Consumer and Producer Price Index
series. However, seasonally adjusted in
dexes are not published for the U.S. aver
age All-Items CPI. Only seasonally adjusted
percent changes are available for this series.
Adjustments for price changes. Some
data— such as the “real” earnings shown in
table 14— are adjusted to eliminate the ef
fect o f changes in price. These adjustments
are made by dividing current-dollar values
by the Consumer Price Index or the appro
80
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Federal Reserve Bank of St. Louis
priate component of the index, then multi
plying by 100. For example, given a current
hourly wage rate o f $3 and a current price
index number o f 150, where 1982 = 100,
the hourly rate expressed in 1982 dollars is
$2 ($3/150 x 100 = $2). The $2 (or any other
resulting values) are described as “real,”
“constant,” or “ 1982” dollars.
Sources of information
Data that supplement the tables in this sec
tion are published by the Bureau in a vari
ety of sources. Definitions o f each series and
notes on the data are contained in later sec
tions of these Notes describing each set of
data. For detailed descriptions of each data
series, see b l s Handbook of Methods, Bul
letin 2414. Users also may wish to consult
Major Programs of the Bureau of Labor Sta
tistics, Report 871. News releases provide
the latest statistical information published
by the Bureau; the major recurring releases
are published according to the schedule ap
pearing on the back cover of this issue.
More information about labor force, em
ployment, and unemployment data and the
household and establishment surveys under
lying the data are available in the Bureau’s
monthly publication, Employment and
Earnings. Historical unadjusted data from
the household survey are published in La
bor Force Statistics Derived From the Cur
rent Population Survey, BLS Bulletin 2307.
H istorical seasonally adjusted data are
available from the Bureau upon request.
Historically comparable unadjusted and sea
sonally adjusted data from the establishment
survey are published in Employment, Hours,
and Earnings, United States, a BLS annual
bulletin. Additional information on labor
force data for sub-States are provided in the
BLS annual report, Geographic Profile of
More detailed data on consumer and pro
ducer prices are published in the monthly
periodicals, The CPI Detailed Report and
Producer Price Indexes. For an overview of
the CPI reflecting 1982-84 expenditure pat
terns, see The Consumer Price Index: 1987
Revision, b l s Report 736. Additional data
on international prices appear in monthly
news releases.
For a listing of available industry pro
ductivity indexes and their components, see
Productivity Measures fo r Selected Indus
tries and Government Services, BLS Bulle
tin 2440.
For additional information on interna
tional comparisons data, see International
Comparisons of Unemployment, BLS Bulle
tin 1979.
Detailed data on the occupational injury
and illness series are published in Occupa
tional Injuries and Illnesses in the United
States, by Industry’, a BLS annual bulletin.
Finally, the Monthly Labor Review car
ries analytical articles on annual and longer
term developments in labor force, employ
ment, and unemployment; employee com
pensation and collective bargaining; prices;
productivity; international comparisons; and
injury and illness data.
Symbols
n.e.c. = not elsewhere classified,
n.e.s. = not elsewhere specified.
p = preliminary. To increase the time
liness of some series, preliminary
figures are issued based on repre
sentative but incomplete returns,
r = revised. Generally, this revision
reflects the availability o f later
data, but may also reflect other ad
justments.
Employment and Unemployment.
More detailed information on employee
compensation and co llective bargaining
settlements is published in the monthly pe
riodical, Compensation and Working Con
ditions. For a comprehensive discussion of
the Employment Cost Index, see Employ
ment Cost Indexes and Levels, 1975-93,
BLS
Bulletin 2447. The most recent data from
the Employee Benefits Survey appear in the
following Bureau o f Labor Statistics bulle
tins: Employee Benefits in Medium and Large
Firms; Employee Benefits in Small Private
Establishments; and Employee Benefits in
State and Local Governments. Historical
data on the collective bargaining settlements
series appear in the March issue o f Com
pensation and Working Conditions.
August 1995
Comparative Indicators
(Tables 1-3)
Comparative indicators tables provide an
overview and comparison of major b l s sta
tistical 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 em
ployment measures from two major surveys
and information on rates of change in com
pensation provided by the Employment Cost
Index (ECi) program. The labor force partici
pation rate, the employment-to-population
ratio, and unemployment rates for major
demographic groups based on the Current
Population (“household”) Survey are pre
sented, while measures of employment and
average weekly hours by major industry sec
tor are given using nonfarm payroll data. The
Employment Cost Index (compensation), by
major sector and by bargaining status, is
chosen from a variety of b l s compensation
and wage measures because it provides a
comprehensive measure o f employer costs
for hiring labor, not just outlays for wages,
and it is not affected by employment shifts
among occupations and industries.
Data on changes in compensation,
prices, and productivity are presented in
table 2. Measures of rates of change o f com
pensation 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 o f changes in
consumer prices for all urban consumers;
producer prices by stage of processing; over
all prices by stage of processing; and overall
export and import price indexes are given.
Measures o f productivity (output per hour of
all persons) are provided for major sectors.
Alternative measures of wage and
compensation rates of change, which re
flect the overall trend in labor costs, are
summarized in table 3. Differences in con
cepts and scope, related to the specific
purposes o f 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.
Em ploym ent an d
U nem ploym ent D ata
(Tables 1; 4-20)
Household survey d ata
Description of the series
in this section are ob
tained from the Current Population Survey,
a program of personal interviews conducted
monthly by the Bureau o f the Census for the
Bureau of Labor Statistics. The sample con
sists of about 60,000 households selected to
represent the U.S. population 16 years of age
and older. Households are interviewed on a
rotating basis, so that three-fourths o f the
sample is the same for any 2 consecutive
months.
E m p l o y m e n t data
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Federal Reserve Bank of St. Louis
Definitions
tio is employment as a percent of the civil
Employed persons include (1) all those
who worked for pay any time during the
week which includes the 12th day o f the
month or who worked unpaid for 15 hours
or more in a family-operated enterprise and
(2) those who were temporarily absent from
their regular jobs because of illness, vaca
tion, industrial dispute, or similar reasons.
A person working at more than one job is
counted only in the job at which he or she
worked the greatest number of hours.
Unemployed persons are those who did
not work during the survey week, but were
available for work except for temporary ill
ness and had looked for jobs within the pre
ceding 4 weeks. Persons who did not look
for work because they were on layoff are also
counted among the unemployed. The unem
ployment rate represents the number unem
ployed as a percent of the civilian labor force.
The civilian labor force consists of all
employed or unemployed persons in the ci
vilian noninstitutional population. Persons
not in the labor force are those not classi
fied as employed or unemployed. This group
includes discouraged workers, defined as
persons who want and are available for a
job and who have looked for work sometime
in the 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 look
ing, because they believe there are no jobs
available or there are none for which they
w ould qualify. The civilian nonin
stitutional population comprises all per
sons 16 years of age and older who are not
inmates of penal or mental institutions, sani
tariums, or homes for the aged, infirm, or
needy. The civilian labor force participa
tion rate is the proportion o f the civilian
nonin-stitutional population that is in the la
bor force. The employment-population ra-
Revisions to household data
Data relating to 1994 and subsequent
years are not directly comparable with
data for 1993 and earlier years because
of the introduction o f a major redesign of
the survey questionnaire and collection
methodology, and the introduction o f
1990 census-based population controls,
adjusted for the estimated undercount. An
explanation of the changes and their ef
fect on labor force data appears in the
February 1994 issue of Employment and
Earnings, a monthly publication of the
Bureau of Labor Statistics.
Seasonally adjusted data for 1994
were revised at the end of 1994. Addi
tional information on the revisions ap
pears in the January 1995 issue of Em
ployment and Earnings.
ian noninstitutional population.
Notes on the data
From time to time, and especially after a de
cennial census, adjustments are made in the
Current Population Survey figures to correct
for estimating errors during the intercensal
years. These adjustments affect the compa
rability of historical data. A description of
these adjustments and their effect on the
various data series appears in the Explana
tory 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 season
ally adjusted with a procedure called X -ll
a r i m a which was developed at Statistics
Canada as an extension of the standard X11 method previously used by b l s . A de
tailed description of the procedure appears
in the X - 11 a r i m a Seasonal Adjustment
Method, by Estela Bee Dagum (Statistics
Canada, Catalogue No. 12-564E, January
1983).
At the end o f each calendar year, season
ally adjusted data for the previous 5 years
usually are revised, and projected seasonal
adjustment factors are calculated for use
during the January-June period. Because of
the changes introduced into the CPS in Janu
ary 1994, only seasonally adjusted data for
1994 were revised at the end of 1994. In
July, new seasonal adjustment factors,
which incorporate the experience through
June, are produced for the July-December
period, but no revisions are made in the his
torical data.
F o r a d d i t i o n a l i n f o r m a t io n on national
household survey data, contact the Division
of Labor Force Statistics: (202) 606-6378.
Establishment survey d ata
Description of the series
E m p l o y m e n t , h o u r s , a n d e a r n i n g s d a t a in
this section are com piled from payroll
records reported monthly on a voluntary ba
sis to the Bureau o f Labor Statistics and its
cooperating State agencies by about 390,000
establishments representing all industries
except agriculture. Industries are classified
in accordance with the 1987 Standard In
dustrial 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 necessar
ily a firm; it may be a branch plant, for ex
ample, or warehouse.) Self-employed per
sons and others not on a regular civilian pay
roll are outside the scope o f the survey
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Current Labor Statistics
because they are excluded from establish
ment records. This largely accounts for the
difference in employment figures between
the household and establishment surveys.
Definitions
An establishment is an econom ic unit
which produces goods or services (such as a
factory or store) at a single location and is
engaged in one type of economic activity.
Employed persons are all persons who
received pay (including holiday and sick
pay) for any part of the payroll period in
cluding 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 pro
duction operations. Those workers men
tioned in tables 11-16 include production
workers in manufacturing and mining; con
struction workers in construction; and nonsupervisory workers in the following indus
tries: transportation and public utilities;
wholesale and retail trade; finance, insur
ance, 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
for overtime or late-shift work but exclud
ing irregular bonuses and other special
payments. Real earnings are earnings ad
justed to reflect the effects o f changes in
consumer prices. The deflator for this series
is derived from the Consumer Price Index
for Urban Wage Earners and Clerical Work
ers (CPI-W).
Hours represent the average w eekly
hours of production or nonsupervisory work
ers for which pay was received, and are dif
ferent 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 pre
miums were paid.
The Diffusion Index represents the per
cent of industries in which employment was
rising over the indicated period, plus onehalf of the industries with unchanged em
ployment; 50 percent indicates an equal bal
ance between industries with increasing and
decreasing employment. In line with Bureau
practice, data for the 1-, 3-, and 6-month
spans are seasonally adjusted, while those
for the 12-month span are unadjusted. Data
are centered within the span. Table 17 pro
vides an index on private nonfarm employ
ment based on 356 industries, and a manu
facturing index based on 139 industries.
These indexes are useful for measuring the
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dispersion of economic gains or losses and
are also economic indicators.
Notes on the data
Establishment survey data are annually ad
justed to comprehensive counts of employ
ment (called “benchmarks”). The latest ad
justment, which incorporated March 1994
benchmarks, was made with the release of
May 1995 data, published in the July 1995
issue o f the Review. Coincident with the
benchmark adjustment, seasonally adjusted
data were revised to reflect the experience
through March 1995. Comparable revisions
in State data (table 11) occurred with the
publication o f January 1995 data. Unad
justed data from April 1994 forward and
seasonally adjusted data from January 1991
forward are subject to revision in future
benchmarks.
The b l s also uses the X - ll a r i m a meth
odology to seasonally adjust establishment
survey data. Beginning in June 1989, pro
jected seasonal adjustment factors are cal
culated and published twice a year. The
change makes the procedure used for the
establishment survey data more parallel
to that used in adjusting the household
survey data. Revisions of data, usually for
the most recent 5-year period, are made once
a year coin cid en t with the benchmark
revisions.
In the establishment survey, estimates for
the most recent 2 months are based on in
complete returns and are published as pre
liminary in the tables (12-17 in the Review).
When all returns have been received, the es
timates are revised and published as “final”
(prior to any benchmark revisions) in the
third month of their appearance. Thus, D e
cember data are published as preliminary in
January and February and as final in March.
For the same reasons, quarterly establish
ment data (table 1) are preliminary for the
first 2 months o f publication and final in the
third month. Thus, fourth-quarter data are
published as preliminary in January and
February and as final in March.
A comprehensive discussion of the dif
ferences between household and establish
ment data on employment appears in Gloria
P. Green, “Comparing employment esti
mates from household and payroll surveys,”
Monthly Labor Review, December 1969,
pp. 9-20.
F o r a d d i t i o n a l in f o r m a t i o n on estab
lishment survey data, contact the Division
of Monthly Industry Employment Statistics:
(202) 606-6555.
lation Survey (CPS) and the Local Area Un
em ploym ent Statistics (LAUS) program,
which is conducted in cooperation with State
employment security agencies.
Monthly estimates o f the labor force,
employment, and unemployment for States
and sub-State areas are a key indicator of
local economic conditions, and form the ba
sis for determining the eligibility of an area
for benefits under Federal economic assis
tance programs such as the Job Training
Partnership Act. Seasonally adjusted unem
ployment rates are presented in table 10.
Insofar as possible, the concepts and defini
tions underlying these data are those used
in the national estimates obtained from the
CPS.
Notes on the data
Data refer to State o f residence. Monthly
data for 11 States— California, Florida, Illi
nois, Massachusetts, Michigan, New York,
New Jersey, North Carolina, Ohio, Pennsyl
vania, and Texas— are obtained directly
from the CPS because the size o f the sample
is large enough to meet b l s standards of
reliability. Data for the remaining 39 States
and the District o f Columbia are derived
using standardized procedures established
by b l s . Once a year, estimates for the 11
States are revised to new population con
trols, usually with publication o f January
estimates. For the remaining States and the
District of Columbia, data are benchmarked
to annual average CPS levels. Data for 1994
are not directly comparable with those for
1993 as a result of the redesign of the c p s
and other methodological changes. See “Re
visions in State and Area Estimates Effec
tive January 1994,” Employment and Earn
ings, March 1994.
For additional information on data in
this series, call (202) 606-6392 (table 10)
or (202) 606-6589 (table 11).
Compensation and
Wage Data
(Tables 1-3; 21-30)
C o m p e n s a t io n a n d w a g e d a t a 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
Unemployment data by State
Description of the series
Description of the series
The Employment Cost Index (ECI) is a
quarterly measure of the rate o f change in
compensation per hour worked and includes
wages, salaries, and employer costs of em-
Data presented in this section are obtained
from two major sources— the Current Popu-
August 1995
ployee benefits. It uses a fixed market
basket of labor—similar in concept to the
Consumer Price Index’s fixed market bas
ket of goods and services—to measure
change over time in employer costs of em
ploying labor.
Statistical series on total compensation
costs, on wages and salaries, and on benefit
costs are available for private nonfarm work
ers excluding proprietors, the self-employed,
and household workers. The total compen
sation costs and wages and salaries series
are also available for State and local gov
ernment workers and for the civilian non
farm 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 non
farm establishments providing about 23,000
occupational observations and 1,000 State
and local government establishments pro
viding 6,000 occupational observations se
lected to represent total employment in each
sector. On average, each reporting unit pro
vides wage and compensation information
on five well-specified occupations. Data are
collected each quarter for the pay period in
cluding the 12th day of March, June, Sep
tember, 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 govern
ments. (Prior to June 1986, the employment
weights are from the 1970 Census of Pop
ulation.) 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 compensa
tion, not employment shifts among indus
tries or occupations with different levels
of wages and compensation. For the bargain
ing status, region, and metropolitan/nonmetropolitan area series, however, employ
ment data by industry and occupation are
not available from the census. Instead, the
1980 employment weights are reallocated
within these series each quarter based on the
current sample. Therefore, these indexes
are not strictly comparable to those for
the aggregate, industry, and occupation
series.
Definitions
Total compensation costs include wages,
salaries, and the employer’s costs for em
ployee benefits.
Wages and salaries consist of earnings
before payroll deductions, including produc
tion bonuses, incentive earnings, commis
sions, and cost-of-living adjustments.
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Benefits include the cost to employers
for paid leave, supplemental pay (includ
ing nonproduction bonuses), insurance, re
tirement and savings plans, and legally re
quired benefits (such as Social Security,
workers’ compensation, and unemployment
insurance).
Excluded from wages and salaries and
employee benefits are such items as payment-in-kind, free room and board, and tips.
Notes on the data
The Employment Cost Index for changes in
wages and salaries in the private nonfarm
economy was published beginning in 1975.
Changes in total compensation cost—wages
and salaries and benefits combined—were
published beginning in 1980. The series of
changes in wages and salaries and for total
compensation in the State and local govern
ment sector and in the civilian nonfarm
economy (excluding Federal employees)
were published beginning in 1981. Histori
cal indexes (June 1981 = 100) of the quar
terly rates of change are presented in the
March issue of the BLS periodical, Compen
sation and Working Conditions.
F or a d d it io n a l inform ation on the
Employment Cost Index, contact the Divi
sion of Employment Cost Trends: (202)
606-6199.
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 6,000 private sector and State
and local government establishments. The
data are presented as a percentage of em
ployees who participate in a certain benefit,
or as an average benefit provision (for
example, the average number of paid holi
days provided to employees per year). Se
lected data from the survey are presented in
table 25.
The survey covers paid leave benefits
such as lunch and rest periods, holidays and
vacations, and personal, funeral, jury duty,
military, parental, and sick leave; sickness
and accident, long-term disability, and life
insurance; medical, dental, and vision care
plans; defined benefit and defined contribu
tion plans; flexible benefits plans; reimburse
ment accounts; and unpaid parental leave.
Also, data are tabulated on the inci
dence of several other benefits, such as
severance pay, child-care assistance, well
ness programs, and employee assistance
programs.
Definitions
Employer-provided benefits are benefits
that are financed either wholly or partly by
the employer. They may be sponsored by a
union or other third party, as long as there is
some employer financing. However, some
benefits that are fully paid for by the em
ployee also are included. For example, long
term care insurance and postretirement life
insurance paid entirely by the employee are
included because the guarantee of insurabil
ity and availability at group premium rates
are considered a benefit.
Participants are workers who are cov
ered by a benefit, whether or not they use
that benefit. If the benefit plan is financed
wholly by employers and requires employ
ees to complete a minimum length of ser
vice for eligibility, the workers are consid
ered 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 pre
determined formulas to calculate a retire
ment benefit, and obligate the employer to
provide those benefits. Benefits are gener
ally 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 partici
pants, and benefits are based on amounts
credited to these accounts.
Tax-deferred savings plans are a type
of defined contribution plan that allow par
ticipants to contribute a portion of their sal
ary to an employer-sponsored plan and de
fer income taxes until withdrawal.
Flexible benefit plans allow employees
to choose among several benefits, such as
life insurance, medical care, and vacation
days, and among several levels of care
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 em
ployed at least 50, 100, or 250 workers, de
pending on the industry (most service
industries were excluded). The survey con
ducted 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
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August 1995
83
Current Labor Statistics
excluded establishments in Alaska and Ha
waii, as well as part-time employees.
Beginning in 1990, surveys of State and
local governments and small establishments
are conducted in even-numbered years and
surveys of medium and large establishments
are conducted in odd-numbered years. The
small establishment survey includes all pri
vate nonfarm establishments with fewer than
100 workers, while the State and local gov
ernment 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 Em
ployee Benefits Survey, contact the Division
of Occupational Pay and Employee Benefit
Levels: (202) 606-6222.
Collective bargaining
settlements
Description of the series
Collective bargaining settlements data pro
vide statistical measures of negotiated
changes (increases, decreases, and zero
change) in wage rates alone and in compen
sation (wages and benefits), quarterly for
private nonagricultural industries and semi
annually for State and local governments.
Wage rate changes cover collective bargain
ing settlements negotiated in the reference
period involving 1,000 or more workers, and
compensation changes cover settlements
reached in the reference period involving
5,000 or more workers. These data are not
seasonally adjusted and are calculated using
information obtained from bargaining agree
ments on file with the Bureau, parties to the
agreements, and secondary sources, such as
newspaper accounts.
The wage and compensation rate changes
are the percent difference between the aver
age rate per work hour just prior to the start
of a new agreement and the average rate per
work hour that would exist at the end of the
first 365 days of the new agreement (firstyear measure) or at its expiration date (overthe-life measure). These data exclude lump
sum payments.
The compensation cost change is the per
cent difference between the average cost of
compensation per work hour, including the
hourly cost of lump-sum payments made dur
ing the term of the expiring agreement, just
prior to the start of a new agreement and the
average cost of compensation per work hour
under the settlement. The timing of the
changes in compensation rates is reflected
in the compensation cost series, but not in
compensation rate series.
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Federal Reserve Bank of St. Louis
Data on changes in settlements exclude
potential changes under cost-of-living adjust
ment clauses. Averages reflect the change
under each settlement weighted by the num
ber of workers covered. Estimates of changes
are based on the assumption that conditions
existing at the time of the settlement (for
example, composition of the labor force or
methods of funding pensions) will remain
constant over the term of the agreement.
Wage rate changes under all major
agreements (those covering 1,000 or more
workers) measure all wage increases, de
creases, and zero changes occurring in the
reference period, regardless of the settle
ment date. Included are changes from settle
ments reached in the calendar year, changes
deferred from settlements negotiated in ear
lier years, and changes under cost-of-living
adjustment (COLA) clauses. The change in
the wage rate for each agreement is the per
cent difference between the average wage
rate just prior to the start of the reference
period and the average wage rate at the end
of the reference period. The change for each
agreement is weighted .by the number of
workers covered to determine the average
change under all agreements.
Definitions
Wage rate is the average straight-time
hourly wage rate plus shift premiums.
Compensation rates include the wage
rate, premium pay (for example, for over
time and holidays); paid leave; life, health,
and sickness and accident insurance; pen
sion and other retirement plans; severance
pay; and legally required benefits.
Compensation costs include the items
covered by compensation rates plus speci
fied lump-sum payments, the cost of
contractually required training programs that
are not a cost of doing business, and the ad
ditional costs of changes in legally required
insurance known at the time of settlement
to be mandated during the contract term.
Cash payments include wages and
lump-sum payments.
Contingent pay provisions are clauses
which could provide compensation changes
beyond those sp ecified in the settlement.
cola c la u se s and lum p-sum p ro v isio n s
that call for a paym ent on ly if a c o m
pany’s profits exceed a specific amount are
exam ples.
August 1995
Professional and white-collar employees,
for example, make up a much larger propor
tion of the workers covered by government
than by private industry settlements. Lump
sum payments and cola clauses, on the
other hand, are rare in government but com
mon in private industry settlements. Also,
State and local government bargaining fre
quently excludes items such as pension ben
efits and holidays, that are prescribed by
law, while these items are typical bargain
ing issues in private industry.
F or additional information on collec
tive bargaining settlements, contact the Di
vision of Developments in Labor-Manage
ment Relations: (202) 606-6276 (private
industry data) or (202) 606-6280 (State and
local government data).
Work stoppages
Description of the series
Data on work stoppages measure the num
ber and duration of major strikes or lock
outs (involving 1,000 workers or more) oc
curring during the month (or year), the num
ber of workers involved, and the amount of
time lost because of stoppage.
Data are largely from newspaper ac
counts and cover only establishments di
rectly 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 short
ages or lack of service.
Definitions
The number
of strikes and lockouts involving 1,000
workers or more and lasting a full shift or
longer.
Workers involved: The number of
workers directly involved in the stoppage.
Number of days idle: The aggregate
number of workdays lost by workers in
volved in the stoppages.
Number of stoppages:
Days of idleness as a percent of esti
mated working time: Aggregate work
days lost as a percent of the aggregate num
ber of standard workdays in the period mul
tiplied by total employment in the period.
Notes on the data
Notes on the data
Comparisons of major collective bargaining
settlements for State and local government
with those for private industry should note
differences in occupational mix, bargaining
practices, and settlement characteristics.
This series is not comparable with the one
terminated in 1981 that covered strikes in
volving six workers or more.
F or additional information on work
stoppages data, contact the Division of De-
velopments in Labor-Management Rela
tions: (202) 606-6288.
Price D ata
(Tables 2; 31-41)
are gathered by the Bureau
of Labor Statistics from retail and pri
mary markets in the United States. Price in
dexes are given in relation to a base pe
riod—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.
P rice
data
Consumer Price Indexes
Description of the series
The Consumer Price Index (CPI) is a mea
sure of the average change in the prices paid
by urban consumers for a fixed market bas
ket of goods and services. The CPI is calcu
lated 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 ur
ban 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 representa
tive index became apparent. The all-urban
consumer index (CPI-U), introduced in 1978,
is representative of the 1982-84 buying hab
its of about 80 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 cleri
cal workers, the CPI-U covers professional,
managerial, and technical workers, the selfemployed, short-term workers, the unem
ployed, retirees, and others not in the labor
force.
The cpi is based on prices of food, cloth
ing, shelter, fuel, drugs, transportation fares,
doctors’ and dentists’ fees, and other goods
and services that people buy for day-to-day
living. The quantity and quality of these
items are kept essentially unchanged be
tween 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 19,000
retail establishments and 57,000 housing
units in 85 urban areas across the country
are used to develop the “U.S. city average.”
Separate estimates for 15 major urban cen
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Federal Reserve Bank of St. Louis
ters are presented in table 32. 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 differ
ences in the level of prices among cities.
Notes on the data
In January 1983, the Bureau changed the
way in which homeownership costs are
measured 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-owner
ship 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 Janu
ary 1987 data.
F or additional information on con
sumer prices, contact the Division of Con
sumer Prices and Price Indexes: (202)
606-7000.
Producer Price Indexes
Description of the series
Producer Price Indexes (PPi) measure av
erage changes in prices received by domes
tic 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 move
ment of prices of all commodities produced
in the manufacturing; agriculture, forestry,
and fishing; mining; and gas and electricity
and public utilities sectors. The stage-ofprocessing structure of ppi organizes prod
ucts by class of buyer and degree of fabrica
tion (that is, finished goods, intermediate
goods, and crude materials). The traditional
commodity structure of ppi organizes prod
ucts by similarity of end use or material
composition. The industry and product
structure of ppi organizes data in 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 cal
culating Producer Price Indexes apply to the
first significant commercial transaction in
the United States from the production or
central marketing point. Price data are gen
erally collected monthly, primarily by mail
questionnaire. Most prices are obtained di
rectly from producing companies on a vol
untary and confidential basis. Prices gener
ally are reported for the Tuesday of the week
containing the 13th day of the month.
Since January 1992, price changes for
the various commodities have been averaged
together with implicit quantity weights rep
resenting their importance in the total net
selling value 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 compos
ite groups. All Producer Price Index data are
subject to revision 4 months after original
publication.
F or a dd itio nal information on pro
ducer prices, contact the Division of Indus
trial Prices and Price Indexes: (202)
606-7705.
International Price Indexes
Description of the series
The International Price Program produces
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 re
quire 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 manu
factures, and finished manufactures, includ
ing both capital and consumer goods. Price
data for these items are collected primarily
by mail questionnaire. In nearly all cases,
the data are collected directly from the ex
porter or importer, although in a few cases,
prices are obtained from other sources.
To the extent possible, the data gathered
refer to prices at the U.S. border for exports
and at either the foreign border or the U.S.
border for imports. For nearly all products,
the prices refer to transactions completed
during the first week of the month. Survey
respondents are asked to indicate all dis
counts, allowances, and rebates applicable
to the reported prices, so that the price used
in the calculation of the indexes is the ac
tual 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 catego
ries of exports and imports. These catego-
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August 1995
85
Current Labor Statistics
ries are defined according to the five
digit level of detail for the Bureau of Eco
nomic Analysis End-use Classification
(Sue), and the four-digit level of detail for
the Harmonized System. Aggregate import
indexes by country or region of origin are
also available.
bls publishes indexes for selected cat
egories o f 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 impor
tance within each harmonized group and are
then aggregated to the higher level. The val
ues 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 re
late to 1990.
Because a price index depends on the
same items being priced from period to pe
riod, it is necessary to recognize when a
product’s specifications or terms of transac
tion have been modified. For this reason, the
Bureau’s questionnaire requests detailed de
scriptions 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 ob
tain 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 pre
ferred pricing basis 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 ship
ment cost to the port of exportation. An at
tempt is made to collect two prices for im
ports. The first is the import price f.o.b. at
the foreign port of exportation, which is con
sistent 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 associ
ated 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.
F or additional information on inter
national prices, contact the Division of In
ternational Prices: (202) 606-7155.
86
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Productivity D ata
(Tables 2; 42^15)
Business sector and major
sectors
Description of the series
The productivity measures relate real physi
cal output to real input. As such, they en
compass a family of measures which include
single-factor input measures, such as output
per unit of labor input (output per hour) or
output per unit of capital input, as well as
measures of multifactor productivity (output
per unit of combined labor and capital in
puts). 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 com
pensation, unit labor costs, unit nonlabor
payments, and prices are also provided.
Definitions
Output per hour of all persons (labor pro
ductivity) is the value of goods and services
in constant prices produced per hour of la
bor input. Output per unit of capital ser
vices (capital productivity) is the value of
goods and services in constant dollars pro
duced per unit of capital services input.
Multifactor productivity is the value of
goods and services in constant prices pro
duced per combined unit of labor and capi
tal inputs. Changes in this measure reflect
changes in a number of factors which affect
the production process, such as changes in
technology, shifts in the composition of the
labor force, changes in capacity utilization,
research and development, skill and effort
of the work force, management, and so forth.
Changes in the output per hour measures re
flect the impact of these factors as well as
the substitution of capital for labor.
Compensation per hour is the wages
and salaries of employees plus employers’
contributions for social insurance and pri
vate benefit plans, and the wages, salaries,
and supplementary payments for the selfemployed (except for nonfinancial corpora
tions in which there are no self-employed)—
the sum divided by hours at work. Real
compensation per hour is compensation
per hour deflated by the change in Consumer
Price Index for All Urban Consumers.
Unit labor costs are the labor compen
sation costs expended in the production of a
unit of output and are derived by dividing
compensation by output. Unit nonlabor
payments include profits, depreciation,
August 1995
interest, and indirect taxes per unit of out
put. They are computed by subtracting com
pensation of all persons from current-dollar
value of output and dividing by output.
Unit nonlabor costs contain all the compo
nents of unit nonlabor payments except unit
profits.
Unit profits include corporate profits
with inventory valuation and capital con
sumption 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.
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
output. The indexes for capital services and
combined units of labor and capital are
based on changing weights which are aver
ages of the shares in the current and preced
ing year (the Tornquist index-number
formula).
Notes on the data
The output measure for the business sector
is equal to constant-dollar gross national
product, but excludes the rental value of
owner-occupied dwellings, the rest-ofworld sector, the output of nonprofit insti
tutions, the output of paid employees of pri
vate households, general government, and
the statistical discrepancy. Output of the
nonfarm business sector is equal to busi
ness sector output less farming. The mea
sures are derived from data supplied by the
U.S. Department of Commerce’s Bureau of
Economic Analysis and the Federal Re
serve Board. Quarterly manufacturing out
put indexes are adjusted by the Bureau of
Labor Statistics to annual estimates of man
ufacturing output (gross product originat
ing) from the Bureau of Economic Analy
sis. Compensation and hours data are de
veloped from data of the Bureau of Labor
Statistics and the Bureau of Economic
Analysis.
The productivity and associated cost
measures in tables 42^15 describe the rela
tionship between output in real terms and
the labor time and capital services 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 mea
sure 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;
capital investment; level of output; utiliza
tion of capacity, energy, and materials; the
organization of production; managerial skill;
and the characteristics and efforts of the
work force.
FORADDITIONAL INFORMATION On this pro
ductivity series, contact the Division of Pro
ductivity Research: (202) 606-5606.
all persons (including self-employed) are
constructed.
FOR ADDITIONAL INFORMATION on this se
ries, contact the Division of Industry Pro
ductivity Studies: (202) 606-5618.
Industry productivity
measures
Labor force and
unemployment
Description of the series
Description of the series
The bls industry productivity data supple
ment 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 Stan
dard Industrial Classification system. The
industry measures differ in methodology
and data sources from the productivity mea
sures for the major sectors because the in
dustry measures are developed indepen
dently of the National Income and Product
Accounts framework used for the major sec
tor measures.
Tables 46 and 47 present comparative mea
sures of the labor force, employment, and
unemployment—approximating U.S. con
cepts—for the United States, Canada, Aus
tralia, Japan, and several European coun
tries. The unemployment statistics (and, to
a lesser extent, employment statistics) pub
lished by other industrial countries are not,
in most cases, comparable to U.S. unem
ployment statistics. Therefore, the Bureau
adjusts the figures for selected countries,
where necessary, for all known major defi
nitional differences. Although precise com
parability may not be achieved, these ad
justed figures provide a better basis for in
ternational comparisons than the figures
regularly published by each country.
Definitions
Output per employee hour is derived by
dividing an index of industry output by an
index of aggregate hours of all employees.
Output indexes are based on quantifiable
units of products or services, or both, com
bined with value-shared weights. Whenever
possible, physical quantities are used as the
unit of measurement for output. If quantity
data are not available for a given industry,
data on the constant-dollar value of produc
tion are used.
The labor input series consist of the
hours of all employees (production and
nonproduction workers), the hours of all
persons (paid employees, partners, propri
etors, and unpaid family workers), or the
number of employees, depending upon the
industry.
Notes on the data
The industry measures are compiled from
data produced by the Bureau of Labor Sta
tistics, the Departments of Commerce, Inte
rior, and Agriculture, the Federal Reserve
Board, regulatory agencies, trade associa
tions, and other sources.
For most industries, the productivity
indexes refer to the output per hour of all
employees. For some transportation indus
tries, only indexes of output per employee
are prepared. For some trade and service
industries, indexes of output per hour of
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Federal Reserve Bank of St. Louis
International Com parisons
(Tables 46^-8)
Definitions
For the principal U.S. definitions of the la
bor force, employment, and unemploy
ment, see 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. stan
dard of 16 years of age and older. There
fore, the adjusted statistics relate to the
population age 16 and older in France, Swe
den, and from 1973 onward in the United
Kingdom; 15 and older in Canada, Austra
lia, Japan, Germany, Italy, the Netherlands,
and prior to 1973, the United Kingdom; and
14 and older in Italy prior to 1993. The in
stitutional population is included in the de
nominator 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 dif
ferent 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 us
ing 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 (1994), Italy (1986, 1991,
1993), and Sweden (1987, 1993). For the
United States, the break in series reflects a
number of changes in the labor force survey
beginning with data for January 1994. Data
for 1994 are not directly comparable with
those for earlier years. See the Notes sec
tion on Employment and Unemployment
Data of this Review.
For Italy, the 1986 break in series reflects
more accurate enumeration of the number
of people reported as seeking work in the
last 30 days. The impact was to increase the
Italian unemployment rates approximating
U.S. concepts by about 1 percentage point.
In 1991, the survey sample was modified to
obtain more reliable estimates by sex and
age. The impact was to raise the adjusted
Italian unemployment rate by approximately
0.3 percentage point. In 1993, 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 addi
tion, the lower age limit for the labor force
was raised from 14 to 15 years. (Prior to
these changes, bls adjusted Italy’s pub
lished unemployment rate downward by ex
cluding from the unemployed 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 1.1 percentage points.
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 4.5 percent indicated
by the data shown in table 47. This differ
ence is attributable mainly to the incorpora
tion of the 1991 population census bench
marks in the 1993 data. Data for earlier
years have not yet been adjusted to incorpo
rate the 1991 census results.
Sweden introduced a new questionnaire
in 1987. Questions regarding current avail
ability were added and the period of active
M onthly Labor Review
A ugust 1995
87
Current Labor Statistics
workseeking was reduced from 60 days to 4
weeks. These changes result in lowering
Sweden’s unemployment rate by 0.5 percent
age point. 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 ad
justment for population totals was intro
duced. The impact was to raise the unem
ployment rate by approximately 0.5 percent
age point. The data for 1993 onward are not
seasonally adjusted because the previous
seasonal adjustment pattern is not applicable
following the 1993 break in series.
Preliminary estimates by the Swedish
Statistics Bureau indicate that employment
linked for the 1993 break in series declined
by about 5-1/2 percent in 1993, rather than
the nearly 7 percent indicated by the data
shown in table 47.
F or additional information on this se
ries, contact the Division of Foreign Labor
Statistics: (202) 606-5654.
Manufacturing productivity
and labor costs
Description of the series
Table 48 presents comparative measures of
manufacturing labor productivity, hourly
compensation costs, and unit labor costs for
the United States, Canada, Japan, and nine
European countries. These measures are
limited to trend comparisons—that is, in
tercountry series of changes over time—
rather than level comparisons because reli
able international comparisons of the levels
of manufacturing output are unavailable.
The hours and compensation measures re
fer to all employed persons, including selfempoyed persons and unpaid family work
ers, in the United States and Canada and to
all employees (wage and salary earners) in
the other countries.
Definitions
Output, in general, refers to value added in
manufacturing (gross product originating) in
constant prices from the national accounts
of each country. However, output for Japan
prior to 1970 and the Netherlands from 1969
to 1977 are indexes of industrial production.
The national accounts measures for the
United Kingdom are essentially identical to
its indexes of industrial production. While
methods of deriving national accounts mea
sures differ substantially from country to
country, the use of different procedures does
not, in itself, connote lack of comparabil
ity—rather, it reflects differences among
countries in the availability and reliability
of underlying data series.
88
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Hours refer to hours worked in all coun
tries. The measures are developed from sta
tistics of manufacturing employment and
average hours. The series used for France
(from 1970 forward), Norway, and Swe
den are official series published with the
national accounts. Where official total hours
series are not available. The measures are
developed by the Bureau using employ
ment figures published with the national ac
counts, or other comprehensive employment
series, and estimates of annual hours
worked.
Compensation (labor cost) includes all
payments in cash or kind made directly to
employees plus employer expenditures for
legally required insurance programs and
contractual and private benefit plans. In ad
dition, for some countries, compensation is
increased to account for other significant
taxes on payrolls or employment (or reduced
to reflect subsidies), even if they are not for
the direct benefit of workers, because such
taxes are regarded as labor costs. However,
compensation does not include all items of
labor costs. The costs of recruitment, em
ployee training, and plant facilities and ser
vices—such as cafeterias and medical clin
ics—are not covered because data are not
available for most countries. The compen
sation measures are from the national ac
counts, except those for Belgium, which are
developed by the Bureau using statistics on
employment, average hours, and hourly
compensation. Self-employed workers are
included in the U.S. and Canadian compen
sation figures 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 Interna
tional Standard Industrial Classification.
However, the measures for France. Italy (be
ginning 1970), and the United Kingdom (be
ginning 1971) refer to mining and manufac
turing less energy-related products; the mea
sures for Denmark include mining and
exclude manufacturing handicrafts from
1960 to 1966; and the measures for the
Netherlands exclude petroleum refining and
include coal mining from 1969 to 1976.
The figures for one or more recent years
are generally based on current indicators of
manufacturing output (such as industrial
production indexes), employment, average
hours, and hourly compensation and are con
sidered preliminary until the national ac
counts and other statistics used for the long
term measures becomes available.
F or additional information on this se
ries, contact the Division of Foreign Labor
Statistics: (202) 606-5654.
A ugust 1995
O c c u p a tio n a l Injury
a n d Illness D ata
(Table 49)
Description of the series
The Annual Survey of Occupational Injuries
and Illnesses is designed to collect data on
injuries and illnesses based on records
which employers in the following industries
maintain under the Occupational Safety and
Health Act of 1970: agriculture, forestry, and
fishing; oil and gas extraction; construction;
manufacturing; transportation and public
utilities; wholesale and retail trade; finance,
insurance, and real estate; and services. Ex
cluded from the survey are self-employed in
dividuals, farmers with fewer than 11 em
ployees, employers regulated by other Fed
eral safety and health laws, and Federal,
State, and local government agencies.
Because the survey is a Federal-State co
operative program and the data must meet
the needs of participating State agencies, an
independent sample is selected for each
State. The sample is selected to represent
all private industries in the States and terri
tories. The sample size for the survey is de
pendent upon (1) the characteristics for
which estimates are needed; (2) the indus
tries for which estimates are desired; (3) the
characteristics of the population being
sampled; (4) the target reliability of the es
timates; and (5) the survey design employed.
While there are many characteristics upon
which the sample design could be based, the
total recorded case incidence rate is used
because it is one of the most important char
acteristics and the least variable; therefore,
it requires the smallest sample size.
The survey is based on stratified random
sampling with a Neyman allocation and a
ratio estimator. The characteristics used to
stratify the establishments are the Standard
Industrial Classification (SIC) code and size
of employment.
Definitions
Recordable occupational injuries and ill
nesses are: (1) occupational deaths, regard
less of the time between injury and death,
or the length of the illness; or (2) nonfatal
occupational illnesses; or (3) nonfatal occu
pational injuries which involve one or more
of the following: loss of consciousness, re
striction of work or motion, transfer to an
other job, or medical treatment (other than
first aid).
Occupational injury is any injury, such
as a cut, fracture, sprain, amputation, and
so forth, which results from a work accident
or from exposure involving a single incident
in the work environment.
Occupational illness is an abnormal
condition or disorder, other than one result
ing from an occupational injury, caused by
exposure to environmental factors associ
ated with employment. It includes acute and
chronic illnesses or disease which may be
caused by inhalation, absorption, ingestion,
or direct contact.
Lost workday cases are cases which in
volve days away from work, or days of re
stricted work activity, or both.
Lost workday cases involving re
stricted work activity are those cases which
result in restricted work activity only.
Lost workdays away from work are the
number of workdays (consecutive or not) on
which the employee would have worked but
could not because of occupational injury or
illness.
Lost workdays—restricted work activ
ity are the number of workdays (consecutive
or not) on which, because of injury or illness:
(1) the employee was assigned to another job
on a temporary basis; (2) the employee
worked at a permanent job less than full time;
or (3) the employee worked at a permanently
assigned job but could not perform all du
ties normally connected with it.
The number of days away from work or
days of restricted work activity does not in
clude the day of injury or onset of illness or
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Federal Reserve Bank of St. Louis
any days on which the employee would not
have worked even though able to work.
Incidence rates represent the number of
injuries and/or illnesses or lost workdays per
100 full-time workers.
Notes on the data
Estimates are made for industries and em
ployment-size classes and for severity clas
sification: fatalities, lost workday cases, and
nonfatal cases without lost workdays. Lost
workday cases are separated into those in
which the employee would have worked but
could not and those in which work activity
was restricted. Estimates of the number of
cases and the number of days lost are made
for both categories.
Most of the estimates are in the form of
incidence rates, defined as the number of
injuries and illnesses or lost workdays per
100 full-time employees. For this purpose,
200,000 employee hours represent 100 em
ployee years (2,000 hours per employee).
Full detail of the available measures is pre
sented in the annual bulletin, Occupational
Injuries and Illnesses in the United States,
by Industry.
Comparable data for individual States
are available from the bls Office of Safety,
Health, and Working Conditions.
Mining and railroad data are furnished
to BLS by the Mine Safety and Health Ad
ministration and the Federal Railroad Ad
ministration. Data from these organizations
are included in bls and State publications.
Federal employees experience is compiled
and published by the Occupational Safety and
Health Administration. Data on State and
local government employees are collected by
about half of the States and territories; these
data are not compiled nationally.
The Supplementary Data System pro
vides detailed information describing vari
ous factors associated with work-related in
juries and illnesses. These data are obtained
from information reported by employers to
State workers’ compensation agencies. The
Work Injury Report program examines se
lected types of accidents through an em
ployee survey which focuses on the circum
stances surrounding the injury. These data
are available from the bls Office of Safety,
Health, and Working Conditions.
The definitions of occupational injuries
and illnesses and lost workdays are from
Recordkeeping Requirements under the Oc
cupational Safety and Health Act of 1970.
F or additional information on occupa
tional injuries and illnesses, contact the Di
vision of Safety and Health Statistics: (202)
606-6166.
M onthly Labor Review
A ugust 1995
89
Current Labor Statistics:
1.
C o m p a ra tiv e Indicators
Labor market indicators
1993
Selected indicators
1993
1994
1995
1994
II
III
IV
I
II
III
IV
I
Employment data1
Employment status of the civilian noninstitutionalized population
(household survey):2
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............................................................
66.2
61.6
6.8
7.1
14.3
5.8
6.5
12.2
5.4
66.6
62.5
6.1
6.2
13.2
4.8
6.0
11.6
4.9
66.2
61.6
7.0
7.3
14.9
5.8
6.6
12.6
5.4
66.1
61.7
6.7
7.1
14.2
5.8
6.4
11.7
5.3
66.2
61.9
6.5
6.7
13.5
5.5
6.3
11.6
5.3
66.7
62.3
6.6
6.7
14.1
5.2
6.4
12.1
5.3
66.5
62.4
6.2
6.2
13.3
4.8
6.2
11.9
5.0
66.5
62.5
6.0
6.0
13.1
4.7
5.9
11.6
4.8
66.6
62.9
5.6
5.6
12.2
4.4
5.6
11.0
4.5
66.9
63.2
5.5
5.5
11.9
4.2
5.6
11.2
4.4
Total .....................................................................................
Private sector......................................................................
Goods-producing..................................................................
Manufacturing....................................................................
Service-producing ................................................................
110,730
91,889
23,352
18,075
87,378
114,034
94,917
23,913
18,303
90,121
110,354
91,550
23,301
18,064
87,052
111,021
92,143
23,345
18,049
87,676
111,816
92,877
23,481
18,096
88,335
112,655
93,656
23,646
18,181
89,008
112,995
93,990
23,534
18,020
89,461
114,481
95,314
23,978
18,333
90,503
115,329
96,099
24,162
18,436
91,167
116,078
96,841
24,329
18,517
91,749
Average hours:
Private sector ......................................................................
Manufacturing .................................................................
Overtime........................................................................
34.5
41.4
4.1
34.7
42.0
4.7
34.5
41.3
4.1
34.5
41.5
4.1
34.5
41.7
4.4
34.6
41.7
4.5
34.7
42.1
4.7
34.7
42.0
4.7
34.7
42.1
4.8
34.7
42.1
4.8
Percent change in the ECI, compensation:
All workers (excluding farm, household, and Federal workers) .....
Private industry workers .......................................................
Goods-producing3............................................................
Service-producing3 ...........................................................
State and local government workers.....................................
3.5
3.6
3.9
3.6
2.8
3.0
3.1
3.1
2.9
3.0
.7
.8
.9
.8
.3
1.0
.9
.7
1.0
1.5
.6
.6
.6
.7
.4
.9
1.0
1.0
.9
.6
.7
.8
1.0
.7
.4
1.0
.8
.7
.9
1.5
.4
.4
.3
.4
.5
.8
.8
.8
.9
.6
Workers by bargaining status (private industry):
Union.................................................................................
Nonunion ...........................................................................
4.3
3.5
2.7
3.1
1.1
.8
.8
.9
.8
.6
.8
1.0
.9
.8
.7
.8
.3
.4
.7
.9
Employment, nonfarm (payroll data), in thousands:2
Employment Cost Index
1 Data for 1994 are not directly comparable with data for 1993 and prior years. For
additional information, see the box note under “Employment and Unemployment Data” in
the notes to this section.
90
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Federal Reserve Bank of St. Louis
August 1995
2 Quarterly data seasonally adjusted.
3 Goods-producing industries include mining, construction, and manufacturing. Serviceproducing industries include all other private sector industries.
2.
Annual and quarterly percent changes in compensation, prices, and productivity
1994
1993
Selected measures
Compensation data:
1993
1995
1994
II
III
IV
I
II
III
IV
I
2
Employment Cost Index-compensation (wages, salaries,
benefits):
Civilian nonfarm ...........................................................
Private nonfarm ..........................................................
Employment Cost Index-wages and salaries
Civilian nonfarm ...........................................................
Private nonfarm ..........................................................
3.5
3.6
3.0
3.1
0.7
.8
1.0
.9
0.6
.6
0.9
1.0
0.7
.8
1.0
.8
0.4
.4
0.8
.8
3.1
3.1
2.8
2.8
.6
.6
1.0
1.0
.6
.6
.6
.7
.7
.8
1.0
.8
.5
.5
.7
.8
Consumer Price Index (All urban consumers): All items.....
2.7
2.7
.5
.5
1.0
.5
.9
.2
1.1
.7
Producer Price Index:
Finished goods............................................................
Finished consumer goods............................................
Capital equipment ......................................................
Intermediate materials, supplies, components .................
Crude materials...........................................................
.2
-.2
1.8
1.0
.1
1.7
1.6
2.0
4.4
-.5
-1.4
-1.5
-.5
.1
-3.1
.2
-.2
1.7
-.7
.0
.6
.6
.8
.7
3.1
.6
.6
.4
1.2
-.9
.0
.2
-.5
1.6
-3.4
.5
.3
1.2
.8
.8
.6
.5
.7
2.1
1.8
1.0
1.2
.4
1.8
1.1
1.3
1.3
2.8
2.4
2.2
2.5
.6
.4
4.6
2.2
2.9
3.2
5.0
4.2
3.9
1.8
1.7
2.0
-1.4
-1.4
-.8
3.2
2.7
1.6
4.3
4.3
3.4
2.2
2.7
1.8
Price data:1
Productivity data:3
Output per hour of all persons:
Business sector..........................................................
Nonfarm business sector.............................................
Nonfinancial corporations 4..........................................
1 Annual changes are December-to-December change. 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.
3 Annual rates of change are computed by comparing annual averages.
Quarterly percent changes reflect annual rates of change in quarterly in
dexes. The data are seasonally adjusted.
4 Output per hour of all employees.
Alternative measures of wage and compensation changes
Quarterly average
Components
1994
1993
IV
Four quarters ended-
I
II
III
IV
1995
1993
I
IV
1994
I
II
1995
IV
. Ill
I
Average hourly compensation:1
All persons, business sector.........................................................
All persons, nonfarm business sector............................................
1.7
1.6
5.1
4.9
0.9
1.4
3.1
2.7
3.6
3.8
4.0
4.3
2.3
1.9
2.9
2.6
2.3
2.3
2.7
2.6
3.2
3.2
2.9
3.0
Employment Cost Index-compensation:
Civilian nonfarm 2 .......................................................................
Private nonfarm ........................................................................
Union ....................................................................................
Nonunion...............................................................................
State and local governments......................................................
.6
.6
.8
.6
.4
.9
1.0
.8
1.0
.6
.7
.8
.9
.8
.4
1.0
.8
.7
.8
1.5
.4
.4
.3
.4
.5
.8
.8
.7
.9
.6
3.5
3.6
4.3
3.5
2.8
3.2
3.3
3.5
3.3
2.8
3.2
3.4
3.3
3.4
2.9
3.2
3.3
3.2
3.3
3.0
3.0
3.1
2.7
3.1
3.0
2.9
2.9
2.6
3.0
3.1
Employment Cost Index-wages and salaries:
Civilian nonfarm2 ........................................................................
Private nonfarm .......................................................................
Union....................................................................................
Nonunion...............................................................................
State and local governments.......................................................
.6
.6
.8
.6
.3
.6
.7
.7
.7
.6
.7
.8
.9
.8
.2
1.0
.8
.9
.8
1.7
.5
.5
.4
.5
.5
.7
.8
.6
.8
.7
3.1
3.1
3.0
3.1
2.7
2.9
2.9
3.0
2.9
2.7
3.0
3.1
3.2
3.0
2.8
2.9
2.9
3.3
2.8
2.9
2.8
2.8
2.9
2.7
3.1
3.0
2.9
2.8
2.9
3.2
.7
.5
.2
.4
.1
.3
.8
.2
.6
.1
.9
.1
.7
.1
.6
.2
.3
.1
.3
.2
3.0
.9
1.9
.2
2.9
.9
1.8
.2
2.7
.9
1.7
.2
2.9
.8
1.9
.2
2.7
.6
1.9
.2
2.6
.5
1.9
,3
Total effective wage adjustments3......................................................
From current settlements.............................................................
From prior settlements................................................................
From cost-of-living provision.........................................................
(4)
(4)
(4)
(4)
Negotiated wage adjustments from settlements:3
First-year adjustments .................................................................
Annual rate over life of contract...................................................
2.8
2.0
3.0
2.4
2.0
2.4
1.0
1.9
2.2
2.5
1.9
1.9
2.3
2.1
2.4
2.1
2.2
2.1
2.3
2.2
2.0
2.3
1.8
2.3
Negotiated wage and benefit adjustments from settlements:5
First-year adjustment ...................................................................
Annual rate over life of contract...................................................
3.8
2.5
3.0
2.6
3.4
2.9
(4)
1.4
1.5
2.1
1.4
1.6
3.0
2.4
3.0
2.3
3.1
2.4
3.1
2.5
2.3
2.4
2.1
2.3
1 Seasonally adjusted.
2 Excludes Federal and household workers.
3 Limited to major collective bargaining units of 1,000 workers or more. The
most recent data are preliminary.
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
4 Data round to zero.
5 Limited to major collective bargaining units of 5,000 workers or more. The
most recent data are preliminary.
M onthly Labor Review
August 1995
91
Current Labor Statistics:
4.
Labor Force D ata
Employment status of the population, by sex, age, race and Hispanic origin, monthly data seasonally adjusted
(Numbers in thousands)
Annual average
1994
1995
Employment status
1994
1993
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
TOTAL
Civilian noninstitutional
population'................................
Civilian labor force....................
Participation rate ...............
Employed..............................
Employment-population
ratio2 ...............................
Unemployed...........................
Unemployment rate............
Not in labor force .....................
193,550 196,814 196,510 196,693 196,859 197,043 197,248 197,430 197,607 197,765 197,753 197,886 198,007 198,148 198,286
128,040 131,056 130,699 130,538 130,774 131,086 131,291 131,646 131,718 131,725 132,136 132,308 132,511 132,737 131,811
66.6
66.4
66.4
66.2
66.5
66.5
66.6
66.7
66.7
66.8
66.6
66.9
66.9
67.0
66.5
119,306 123,060 122,703 122,635 122,781 123,197 123,644 124,141 124,403 124,570 124,639 125,125 125,274 125,072 124,319
61.6
8,734
6.8
65,509
62.5
7,996
6.1
65,758
62.4
7,996
6.1
65,811
62.3
7,903
6.1
66,155
62.4
7,993
6.1
66,085
62.5
7,889
6.0
65,957
62.7
7,647
5.8
65,957
62.9
7,505
5.7
65,784
63.0
7,315
5.6
65,889
63.0
7,155
5.4
66,040
63.0
7,498
5.7
65,617
63.2
7,183
5.4
65,578
63.3
7,237
5.5
65,496
63.1
7,665
5.8
65,412
62.7
7,492
5.7
66,476
85,907
66,069
76.9
61,865
87,151
66,921
76.8
63,294
87,000
66,652
76.6
63,080
87,095
66,602
76.5
63,043
87,123
66,747
76.6
63,076
87,248
66,817
76.6
63,271
87,321
66,909
76.6
63,517
87,439
67,177
76.8
63,820
87,529
67,345
76.9
64,051
87,617
67,450
77.0
64,281
87,528
67,539
77.2
64,133
87,572
67,552
77.1
64,478
87,622
67,643
77.2
64,465
87,664
67,563
77.1
64,224
87,691
67,250
76.7
63,841
72.0
2,263
59,602
4,204
6.4
72.6
2,351
60,943
3,627
5.4
72.5
2,384
60,696
3,572
5.4
72.4
2,334
60,709
3,559
5.3
72.4
2,314
60,762
3,671
5.5
72.5
2,377
60,894
3,546
5.3
72.7
2,293
61,224
3,392
5.1
73.0
2,329
61,491
3,357
5.0
73.2
2,377
61,674
3,294
4.9
73.4
2,410
61,871
3,169
4.7
73.3
2,390
61,743
3,406
5.0
73.6
2,512
61,965
3,074
4.6
73.6
2,519
61,946
3,178
4.7
73.3
2,384
61,840
3,339
4.9
72.8
2,242
61,599
3,410
5.1
94,388
55,146
58.4
51,912
95,467
56,655
59.3
53,606
95,329
56,545
59.3
53,481
95,407
56,384
59.1
53,328
95,469
56,536
59.2
53,541
95,544
56,747
59.4
53,722
95,658
57,031
59.6
54,044
95,729
56,951
59.5
54,090
95,821
56,984
59.5
54,129
95,873
56,725
59.2
54,037
95,961
56,951
59.3
54,134
96,020
57,096
59.5
54,334
96,037
57,042
59.4
54,242
96,099
57,360
59.7
54,403
96,141
56,819
59.1
54,097
55.0
599
51,313
3,234
5.9
56.2
809
52,796
3,049
5.4
56.1
789
52,692
3,064
5.4
55.9
739
52,589
3,056
5.4
56.1
790
52,751
2,995
5.3
56.2
815
52,907
3,025
5.3
56.5
847
53,197
2,987
5.2
56.5
863
53,227
2,861
5.0
56.5
850
53,279
2,855
5.0
56.4
882
53,155
2,688
4.7
56.4
877
53,257
2,817
4.9
56.6
898
53,436
2,763
4.8
56.5
913
53,329
2,800
4.9
56.6
925
53,477
2,957
5.2
56.3
828
53,268
2,722
4.8
13,255
6,826
51.5
5,530
14,196
7,481
52.7
6,161
14,181
7,502
52.9
6,142
14,191
7,552
53.2
6,264
14,267
7,491
52.5
6,164
14,251
7,522
52.8
6,204
14,269
7,351
51.5
6,083
14,261
7,518
52.7
6,231
14,257
7,389
51.8
6,223
14,274
7,550
52.9
6,252
14,263
7,646
53.6
6,372
14,294
7,660
53.6
6,313
14,348
7,826
54.5
6,567
14,385
7,814
54.3
6,446
14,454
7,742
53.6
6,381
41.7
212
5,317
1,296
19.0
43.4
249
5,912
1,320
17.6
43.3
240
5,902
1,360
18.1
44.1
221
6,043
1,288
17.1
43.2
229
5,935
1,327
17.7
43.5
244
5,960
1,318
17.5
42.6
271
5,812
1,268
17.2
43.7
302
5,929
1,287
17.1
43.6
273
5,950
1,166
15.8
43.8
240
6,012
1,298
17.2
44.7
308
6,064
1,274
16.7
44.2
245
6,068
1,347
17.6
45.8
266
6,300
1,260
16.1
44.8
285
6,160
1,369
17.5
44.1
287
6,094
1,360
17.6
Men, 20 years and over
Civilian noninstitutional
population'...............................
Civilian labor force....................
Participation rate ...............
Employed ..............................
Employment-population
ratio2 ...............................
Agriculture ...........................
Nonagricultural industries......
Unemployed...........................
Unemployment rate............
Women, 20 years ond over
Civilian noninstitutional
population'...............................
Civilian labor force....................
Participation rate ...............
Employed ..............................
Employment-population
ratio2 ...............................
Agriculture ...........................
Nonagricultural industries......
Unemployed...........................
Unemployment rate............
Both sexes, 16 to 19 years
Civilian noninstitutional
population'...............................
Civilian labor force....................
Participation rate ...............
Employed ..............................
Employment-population
ratio2 ...............................
Agriculture ...........................
Nonagricultural industries......
Unemployed...........................
Unemployment rate............
White
Civilian noninstitutional
population’ ...............................
Civilian labor force....................
Participation rate ...............
Employed ..............................
Employment-population
ratio2 ...............................
Unemployed...........................
Unemployment rate............
163,921 165,555 165,351 165,472 165,576 165,696 165,832 165,954 166,072 166,175 166,361 166,444 166,521 166,613 166,708
109,359 111,082 110,829 110,523 110,911 111,186 111,381 111,555 111,637 111,715 111,876 111,830 111,999 112,153 111,568
66.7
67.1
67.0
66.8
67.0
67.1
67.2
67.2
67.2
67.2
67.2
67.2
67.3
67.3
66.9
102,812 105,190 104,978 104,687 105,006 105,401 105,740 106,010 106,242 106,352 106,366 106,604 106,698 106,500 105,935
62.7
6,547
6.0
63.5
5,892
5.3
63.5
5,851
5.3
63.3
5,836
5.3
63.4
5,905
5.3
63.6
5,785
5.2
63.8
5,641
5.1
63.9
5,545
5.0
64.0
5,395
4.8
64.0
5,363
4.8
63.9
5,510
4.9
64.0
5,226
4.7
64.1
5,301
4.7
63.9
5,653
5.0
63.5
5,633
5.0
22,329
13,943
62.4
12,146
22,879
14,502
63.4
12,835
22,824
14,510
63.6
12,810
22,855
14,481
63.4
12,838
22,883
14,380
62.8
12,767
22,917
14,429
63.0
12,795
22,955
14,477
63.1
12,927
22,990
14,649
63.7
13,022
23,023
14,578
63.3
13,054
23,052
14,541
63.1
13,119
23,089
14,697
63.7
13,192
23,117
14,868
64.3
13,362
23,142
14,818
64.0
13,370
23,169
14,938
64.5
13,337
23,192
14,803
63.8
13,336
54.4
1,796
12.9
56.1
1,666
11.5
56.1
1,700
11.7
56.2
1,643
11.3
55.8
1,613
11.2
55.8
1,634
11.3
56.3
1,550
10.7
56.6
1,627
11.1
56.7
1,524
10.5
56.9
1,422
9.8
57.1
1,505
10.2
57.8
1,505
10.1
57.8
1,448
9.8
57.6
1,601
10.7
57.5
1,467
9.9
Black
Civilian noninstitutional
population'...............................
Civilian labor force....................
Participation rate ...............
Employed..............................
Employment-population
ratio2 ...............................
Unemployed...........................
Unemployment rate............
See footnotes at end of table.
M onthly Labor Review
Digitized for 92
FRASER
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
August 1995
4. Continued— Employment status of the population, by sex, age, race and Hispanic origin, monthly data seasonally adjusted
(Numbers in thousands)
Annual average
1994
Employment status
1995
1993
1994
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
15,753
10,377
65.9
9,272
18,117
11,975
66.1
10,788
18,041
11,916
66.0
10,735
18,092
11,896
65.8
10,682
18,143
11,956
65.9
10,760
18,193
12,002
66.0
10,786
18,244
11,997
65.8
10,806
18,291
12,222
66.8
11,074
18,339
12,324
67.2
11,236
18,385
12,224
66.5
11,105
18,368
12,036
65.5
10,811
18,413
12,017
65.3
10,943
18,458
12,001
65.0
10,903
18,509
12,131
65.5
11,058
18,554
12,111
65.3
10,895
58.9
1,104
10.6
59.5
1,187
9.9
59.5
1,181
9.9
59.0
1,214
10.2
59.3
1,196
10.0
59.3
1,216
10.1
59.2
1,191
9.9
60.5
1,148
9.4
61.3
1,088
8.8
60.4
1,119
9.2
58.9
1,224
10.2
59.4
1,073
8.9
59.1
1,098
9.1
59.7
1,073
8.8
58.7
1,216
10.0
Hispanic origin
Civilian noninstitutional
population'...............................
Civilian labor force....................
Participation rate ...............
Employed ..............................
Employment-population
ratio2 ...............................
Unemployed...........................
Unemployment rate............
' The population tigures are not seasonally adjusted.
2 Civilian employment as a percent of the civilian noninstitutional population.
NOTE: Data for 1994 are not directly comparable with data for 1993 and earlier years.
For additional information, see the box note under “Employment and Unemployment
5.
Data” in the notes to this section.
Detail for the above race and Hispanic-origin groups will not sum to totals because data
for the “other races” groups are not presented and Hispanics are included in both the
white and black population groups.
Selected employment indicators, monthly data seasonally adjusted
(In thousands)
Annual average
1994
Selected categories
1993
1994
May
June
July
Aug.
1995
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
CHARACTERISTIC
Employed, 16 years and over...... 119,306 123,060 122,703 122,635 122,781 123,197 123,644 124,141 124,403 124,570 124,639 125,125 125,274 125,072 124,319
Men ..................................... 64,700 66,450 66,197 66,255 66,226 66,458 66,682 67,059 67,244 67,483 67,386 67,709 67,811 67,588 67,110
Women ............................
54,606 56,610 56,506 56,380 56,555 56,739 56,962 57,082 57,159 57,087 57,252 57,416 57,462 57,484 57,208
Married men, spouse present .. 40,869 41,414 41,330 41,313 41,281 41,487 41,557 41,511 41,530 41,608 41,601 42,190 42,132 42,086 41,874
Married women, spouse
present...............................
30,512 31,536 31,372 31,193 31,462 31,593 31,905 31,764 31,775 31,723 31,705 31,893 32,135 32,108 32,022
Women who maintain families .
6,764
7,053
7,061
7,008
7,016
6,974
7,029
7,098
7,141
7,074
7,199
7,067
7,071
7,152
7,175
CLASS OF WORKER
Agriculture:
Wage end salary workers......
Self-employed workers..........
Unpaid family workers...........
Nonagricultural industries:
Wage and salary workers ......
Government .......................
Private industries................
Private households...........
Other ..........................
Self-employed workers..........
Unpaid family workers...........
1,637
1,332
105
1,715
1,645
49
1,736
1,637
43
1,675
1,584
46
1,669
1,619
50
1,728
1,654
50
1,712
1,630
63
1,764
1,652
43
1,767
1,677
48
1,738
1,714
49
1,866
1,663
35
1,970
1,684
27
1,987
1,674
57
1,884
1,649
70
1,747
1,560
55
107,011 110,517 110,164 110,215 110,345 110,576 111,100 111,686 111,770 111,960 111,987 112,461 112,649 112,578 112,111
18,504 18,293 18,378 18,294 18,281 18,225 18,306 18,201 18,357 18,340 18,295 18,504 18,685 18,646 18,493
88,507 92,224 91,786 91,921 92,064 92,351 92,794 93,485 93,413 93,620 93,692 93,957 93,964 93,932 93,619
1,105
966
978
966
940
881
903
935
999
1,023
1,075
1,075
1,039
988
913
87,402 91,258 90,808 90,955 91,124 91,470 91,891 92,550 92,414 92,597 92,617 92,882 92,925 92,945 92,705
9,003
9,003
9,049
8,964
8,962
9,021
8,989
8,878
8,915
8,959
9,039
8,904
8,865
8,848
8,763
218
131
129
148
140
131
134
131
120
121
95
118
129
110
125
PERSONS AT WORK
PART TIME'
All industries:
Part time for economic reasons .
Slack work or business
conditions............................
Could only find part-time work
Part time for noneconomic
reasons ................................
Nonagricultural industries:
Part time for economic reasons .
Slack work or business
conditions............................
Could only find part-time work
Part time for noneconomic
reasons ................................
6,348
4,625
4,792
4,766
4,467
4,348
4,333
4,411
4,411
4,422
4,693
4,460
4,530
4,469
4,476
3,140
2,908
2,432
1,871
2,503
1,981
2,464
1,927
2,431
1,698
2,396
1,618
2,404
1,697
2,394
1,791
2,394
1,736
2,384
1,734
2,504
1,777
2,372
1,739
2,333
1,902
2,517
1,686
2,502
1,720
15,062
17,638
17,441
17,452
17,922
17,955
17,609
17,644
17,756
17,576
17,940
18,041
17,627
18,121
17,666
6,106
4,414
4,583
4,510
4,273
4,173
4,154
4,226
4,246
4,254
4,430
4,187
4,347
4,171
4,289
2,977
2,832
2,311
1,824
2,386
1,942
2,349
1,883
2,318
1,661
2,272
1,583
2,290
1,646
2,257
1,756
2,282
1,689
2,272
1,690
2,359
1,737
2,216
1,687
2,226
1,854
2,328
1,624
2,364
1,698
14,637
17,007
16,841
16,909
17,308
17,314
16,982
16,992
17,101
16,917
17,307
17,381
16,991
17,232
17,034
1 Excludes persons “with a job but not at work” during the survey period for such reasons as vacation, illness, or industrial disputes.
NOTE:
D a ta f o r 1 9 9 4 a re n o t d ire c tly c o m p a ra b le w ith d a ta fo r 1 9 9 3 a n d e a r lie r y e a rs .
the notes to this section.
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
F o r a d d itio n a l in fo r m a tio n , s e e th e b o x n o te u n d e r “ E m p lo y m e n t a n d U n e m p lo y m e n t D a t a " in
M onthly Labor Review
August 1995
93
Current Labor Statistics:
6.
Labor Force D ata
Selected unemployment indicators, monthly data seasonally adjusted
(Unemployment rates)
1994
Annual average
1995
Selected categories
1993
1994
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
Total, all workers..............................................
Both sexes, 16 to 19 years............................
Men, 20 years and over................................
Women, 20 years and over............................
6.8
19.0
6.4
5.9
6.1
17.6
5.4
5.4
6.1
18.1
5.4
5.4
6.1
17.1
5.3
5.4
6.1
17.7
5.5
5.3
6.0
17.5
5.3
5.3
5.8
17.2
5.1
5.2
5.7
17.1
5.0
5.0
5.6
15.8
4.9
5.0
5.4
17.2
4.7
4.7
5.7
16.7
5.0
4.9
5.4
17.6
4.6
4.8
5.5
16.1
4.7
4.9
5.8
17.5
4.9
5.2
5.7
17.6
5.1
4.8
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.........................
6.0
16.2
17.6
14.6
5.6
5.1
5.3
15.1
16.3
13.8
4.8
4.6
5.3
15.5
17.0
13.7
4.7
4.6
5.3
14.3
15.1
13.6
4.7
4.7
5.3
14.7
16.1
13.1
4.8
4.7
5.2
14.6
15.4
13.7
4.6
4.6
5.1
14.8
16.2
13.3
4.4
4.6
5.0
14.4
15.2
13.5
4.4
4.4
4.8
13.5
14.3
12.6
4.3
4.3
4.8
14.7
16.0
13.2
4.2
4.1
4.9
14.1
15.0
13.1
4.4
4.3
4.7
14.7
16.1
13.1
4.0
4.1
4.7
13.6
14.7
12.4
4.2
4.2
5.0
14.6
15.3
13.8
4.4
4.5
5.0
14.8
15.2
14.3
4.6
4.3
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.........................
12.9
38.9
40.1
37.5
12.1
10.6
11.5
35.2
37.6
32.6
10.3
9.8
11.7
38.2
40.9
35.0
10.3
10.0
11.3
36.1
39.3
32.6
10.0
9.5
11.2
37.3
41.4
32.7
10.4
8.8
11.3
36.1
39.9
31.9
10.2
9.4
10.7
32.1
30.8
33.4
9.8
9.0
11.1
37.5
35.9
39.1
9.5
9.2
10.5
33.0
32.0
34.1
9.2
8.9
9.8
34.6
34.3
35.0
8.3
8.3
10.2
35.5
34.0
37.1
9.2
8.5
10.1
35.7
38.7
32.4
7.9
9.0
9.8
31.2
31.7
30.7
7.8
9.1
10.7
35.6
35.4
35.8
8.9
9.3
9.9
35.1
40.0
30.5
8.8
7.8
Hispanic origin, total.....................................
10.6
9.9
9.9
10.2
10.0
10.1
9.9
9.4
8.8
9.2
10.2
8.9
9.1
8.8
10.0
Married men, spouse present........................
Married women, spouse present....................
Women who maintain families.......................
Full-time workers .........................................
Part-time workers .........................................
4.4
4.6
9.5
7.4
7.4
3.7
4.1
8.9
6.8
7.1
3.7
4.1
8.9
6.1
6.2
3.6
4.2
8.8
6.1
5.9
3,6
4.0
7.9
6.1
6.0
3.5
4.1
8.8
6.0
6.2
3.4
4.0
8.9
5.8
5.8
3.3
4.0
8.9
5.8
5.6
3.2
3.9
8.7
5.6
5.4
3.2
3.7
8.8
5.3
5.9
3.4
3.7
8.9
5.5
6.2
3.0
3.6
8.1
5.3
6.0
3.2
3.9
7.6
5.4
5.8
3.4
4.2
9.0
5.6
6.3
3.4
3.9
8.0
5.6
6.1
7.0
7.3
14.3
7.2
7.1
7.3
5.1
7.8
6.3
5.4
11.8
5.6
5.2
6.0
4.8
7.4
6.4
6.0
11.7
5.6
5.3
5.9
4.9
7.4
6.3
6.1
11.7
5.5
5.2
5.9
4.9
7.2
6.3
6.0
11.1
5.6
5.5
5.8
5.1
7.5
6.1
5.0
10.7
5.3
5.3
5.3
4.8
7.4
6.0
5.1
10.7
5.3
5.3
5.4
4.5
7.0
5.9
4.7
10.7
5.1
4.8
5.6
4.4
7.2
5.9
4.5
10.7
5.1
4.3
6.0
4.6
7.0
5.6
3.9
10.9
4.9
4.6
5.4
4.2
6.7
5.7
5.1
11.7
4.7
4.2
5.4
4.7
6.6
5.5
5.2
10.5
4.4
3.9
5.0
4.5
6.4
5.5
6.1
10.8
4.5
4.2
4.9
4.5
6.2
5.9
4.3
11.8
4.8
4.4
5.4
4.6
6.8
6.0
4.9
12.6
5.5
5.3
6.0
4.0
6.7
4.1
6.5
3.3
11.6
3.6
6.1
3.4
11.3
3.6
6.0
3.5
8.8
3.7
5.9
3.7
8.6
3.7
5.9
3.4
12.1
3.7
5.7
3.6
11.1
4.3
5.5
3.2
11.1
3.4
5.3
3.2
10.3
3.6
5.4
2.7
10.4
2.9
5.2
3.1
11.1
2.9
5.2
3.2
10.7
3.5
5.2
2.8
9.1
3.3
5.3
. 2.7
10.5
3.4
5.6
3.1
11.3
3.7
5.5
2.8
12.5
CHARACTERISTIC
INDUSTRY
Nonagricultural private 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 ..................
NOTE: Data for 1994 are not directly comparable with data for 1993 and earlier years. For additional information, see the box note under “Employment and Unemployment Data” in
the notes to this section.
7.
Duration of unemployment, monthly data seasonally adjusted
(Numbers in thousands)
1994
Annual average
Weeks of unemployment
1995
1993
1994
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
Less than 5 weeks.....................................
5 to 14 weeks ............................................
15 weeks and over.....................................
15 to 26 weeks ........................................
27 weeks and over...................................
3,160
2,522
3,052
1,274
1,778
2,728
2,408
2,860
1,237
1,623
2,651
2,461
2,853
1,160
1,693
2,754
2,452
2,740
1,193
1,547
2,768
2,365
2,823
1,234
1,589
2,655
2,572
2,773
1,198
1,575
2,675
2,294
2,768
1,213
1,555
2,434
2,256
2,934
1,344
1,590
2,599
2,163
2,661
1,187
1,474
2,587
2,149
2,456
1,088
1,368
2,937
2,122
2,386
1,033
1,353
2,600
2,165
2,298
1,090
1,207
2,523
2,319
2,266
920
1,347
2,629
2,430
2,505
1,115
1,390
2,598
2,304
2,585
1,282
1,303
Mean duration, in weeks..............................
Median duration, in weeks............................
18.1
8.4
18.8
9.2
19.4
9.2
18.4
9.1
19.0
9.2
18.9
9.2
18.8
9.5
19.3
10.1
18.2
9.1
17.8
8.7
16.7
7.9
16.9
7.8
17.5
7.9
17.7
8.5
16.9
9.0
NOTE: In the three tables above, data for 1994 are not directly comparable with
data for 1993 and earlier years. For additional information, see the box note under
M onthly Labor Review
94
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
August 1995
“Employment and Unemployment Data" in the notes to this section,
8.
Unemployed persons by reason for unemployment, monthly data seasonally adjusted
(Numbers in thousands)
Annual average
1994
1995
Reason for unemployment
1993
Job losers' .......................................................
On temporary layoff........................................
Not on temporary layoff ..................................
Job leavers ......................................................
Reentrants .......................................................
New entrants ...................................................
1994
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
4,769
1,104
3,664
946
2,145
874
3,815
977
2,838
791
2,786
604
3,640
811
2,829
796
2,863
611
3,734
931
2,803
788
2,785
498
3,863
1,031
2,832
770
2,766
594
3,706
1,012
2,694
786
2,758
621
3,574
824
2,750
874
2,620
600
3,513
848
2,665
755
2,626
614
3,495
881
2,614
710
2,575
578
3,442
930
2,512
704
2,525
555
3,658
1,061
2,598
694
2,488
597
3,339
1,025
2,314
773
2,474
582
3,352
1,032
2,320
811
2,430
604
3,532
1,145
2,387
817
2,779
637
3,614
958
2,657
870
2,458
522
54.6
12.6
42.0
10.8
24.6
10.0
47.7
12.2
35.5
9.9
34.8
7.6
46.0
10.3
35.8
10.1
36.2
7.7
47.8
11.9
35.9
10.1
35.7
6.4
48.3
12.9
35.4
9.6
34.6
7.4
47.1
12.9
34.2
10.0
35.0
7.9
46.6
10.7
35.9
11.4
34.2
7.8
46.8
11.3
35.5
10.1
35.0
8.2
47.5
12.0
35.5
9.6
35.0
7.9
47.6
12.9
34.8
9.7
34.9
7.7
49.2
14.3
34.9
9.3
33.4
8.0
46.6
14.3
32.3
10.8
34.5
8.1
46.6
14.3
32.2
11.3
33.8
8.4
45.5
14.7
30.7
10.5
35.8
8.2
48.4
12.8
35.6
11.7
32.9
7.0
3.7
.7
1.7
.7
2.9
.6
2.1
.5
2.8
.6
2.2
.5
2.9
.6
2.1
.4
3.0
.6
2.1
.5
2.8
.6
2.1
.5
2.7
.7
2.0
.5
2.7
.6
2.0
.5
2.7
.5
2.0
.4
2.6
.5
1.9
.4
2.8
.5
1.9
.5
2.5
.6
1.9
.4
2.5
.6
1.8
.5
2.7
.6
2.1
.5
2.7
.7
1.9
.4
PERCENT OF UNEMPLOYED
Job losers' ....................................................
On temporary layoff .....................................
Not on temporary layoff................................
Job leavers....................................................
Reentrants.....................................................
New entrants .................................................
PERCENT OF
CIVILIAN LABOR FORCE
Job losers' ......................................................
Job leavers ......................................................
Reentrants ......................................................
New entrants ...................................................
1 Includes persons who completed temporary jobs.
9.
Unemployment rates by sex and age, monthly data seasonally adjusted
(Civilian workers)
Sex and age
Annual
average
1993
1994
1994
May
June
July
Aug.
1995
Sept.
Oct.
Nov.
Dec.
Jan.
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...........................................................
6.8
13.3
19.0
21.3
17.5
10.5
5.6
5.8
4.3
6.1
12.5
17.6
19.9
16.0
9.7
4.8
5.0
4.1
6.1
12.6
18.1
20.4
16.3
9.6
4.8
4.9
4.2
6.1
12.2
17.1
20.1
15.4
9.5
4.8
4.9
4.0
6.1
12.5
17.7
20.3
15.7
9.7
4.8
4.9
4.2
6.0
12.6
17.5
19.9
15.6
9.9
4.7
4.8
4.2
5.8
12.1
17.2
18.8
16.0
9.4
4.6
4.8
3.8
5.7
11.8
17.1
17.8
16.8
9.0
4.5
4.7
3.9
5.6
11.4
15.8
17.2
14.7
9.1
4.5
4.5
3.9
5.4
11.6
17.2
18.1
16.6
8.6
4.3
4.4
3.5
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.......................................................
7.1
14.3
20.4
22.8
18.8
11.3
5.8
5.9
4.7
6.2
13.2
19.0
21.0
17.6
10.2
4.8
4.9
4.3
6.2
13.5
19.9
22.4
18.0
10.1
4.7
4.8
4.4
6.0
12.7
18.0
21.6
16.6
9.9
4.8
4.8
4.2
6.3
13.4
19.4
20.9
18.0
10.3
4.9
4.9
4.5
6.1
13.3
18.8
20.7
17.1
10.5
4.7
4.8
4.2
5.8
12.6
18.5
19.4
17.5
9.5
4.5
4.6
3.9
5.7
12.4
18.1
18.2
18.1
9.4
4.5
4.6
4.1
5.5
11.8
16.5
16.5
16.5
9.5
4.4
4.4
4.0
5.5
12.2
18.5
18.8
18.2
9.0
4.3
4.3
3.5
17.4
20.9
14.5
9.1
4.5
4.6
4.0
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 ..........................................................
55 years and over .....................................................
6.5
12.2
17.4
19.6
16.0
9.6
5.4
5.6
3.8
6.0
11.6
16.2
18.7
14.3
9.2
4.9
5.0
3.9
6.1
11.6
16.2
18.3
14.6
9.0
5.0
5.1
3.9
6.1
11.6
16.0
18.5
14.2
9.1
4.9
5.1
3.8
5.9
11.5
15.9
19.7
13.1
9.1
4.8
5.0
3.7
6.0
11.7
16.1
19.0
14.0
9.3
4.8
4.9
4,1
5.8
11.6
15.9
18.2
14.2
9.3
4.7
5.0
3.6
5.7
11.2
16.0
17.4
15.4
8.6
4.6
4.8
3.7
5.6
10.9
15.0
17.9
12.8
8.7
4.6
4.7
3.8
5.4
10.9
15.8
17.4
14.9
8.1
4.3
4.4
3.4
5.6
10.7
15.9
19.1
13.9
7.8
4.6
4.6
3.7
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
5.7
11.4
16.7
20.0
14.2
8.5
4.5
4.6
3.9
5.7
12.0
M onthly Labor Review
Feb.
5.4
11.7
17.6
20.7
15.3
8.5
4.2
4.3
3.4
5.4
Mar.
5.5
5.8
5.7
11.8
11.8
16.1
17.5
20.0
20.6
13.0
9.1
4.2
4.3
3.5
15.7
8.7
4.6
4.7
3.8
17.6
21.5
14.7
11.8
19.4
22.6
20.2
16.7
14.6
8.9
4.1
4.2
3.7
8.2
4.0
4.2
3.6
5.5
11.2
15.6
18.7
13.7
8.7
4.3
4.5
3.2
May
11.6
5.4
11.7
17.0
12.1
Apr.
5.5
11.5
15.2
19.8
11.3
9.4
4.3
4.4
3.4
August 1995
5.7
8.6
4.5
4.6
3.8
5.8
12.3
18.4
17.8
21.7
16.1
22.6
4.5
4.5
4.3
15.2
8.9
4.6
4.7
4.0
5.9
11.9
17.2
19.4
15.2
5.5
11.4
16.7
20.4
14.0
8.6
8.8
8.2
4.7
5.0
3.3
4.4
4.6
3.6
95
Current Labor Statistics:
10.
Labor Force D ata
Unemployment rates by State, seasonally adjusted
May
1994
Apr.
1995
May
1995p
Alabama..............
Alaska..................
Arizona................
Arkansas .............
California.............
6.1
8.0
6.4
5.5
8.5
5.8
6.7
5.5
5.0
7.9
5.9
6.4
5.6
4.1
8.5
Colorado..............
Connecticut..........
Delaware.............
District of Columbia
Florida.................
4.4
5.5
5.1
8.1
6.8
4.0
5.2
4.1
8.4
5.6
3.9
5.1
4.3
8.6
5.1
Georgia...............
Hawaii.................
Idaho...................
Illinois..................
Indiana................
5.2
6.0
5.3
5.8
4.9
4.7
5.2
5.1
5.7
4.8
4.8
5.1
5.1
5.5
4.7
Iowa....................
Kansas................
Kentucky..............
Louisiana.............
Maine..................
3.7
5.2
5.4
8.1
7.0
3.4
4.6
4.8
7.6
5.8
3.3
4.7
5.0
7.1
6.2
Maryland..............
Massachusetts......
Michigan..............
Minnesota............
Mississippi...........
Missouri ...............
5.2
5.8
5.9
4.0
6.6
4.9
4.9
5.9
5.8
3.7
5.5
4.9
5.0
5.0
5.7
3.9
6.0
5.1
State
May
1994
Apr.
1995
May
1995»
Montana............................................
Nebraska...........................................
Nevada ..............................................
New Hampshire .................................
4.9
2.8
6.2
4.8
5.3
2.5
5.8
4.0
5.5
2.6
5.9
3.8
New Jersey........................................
New Mexico.......................................
New York..........................................
North Carolina....................................
North Dakota.....................................
6.9
6.4
6.5
4.2
3.8
6.3
6.0
6.8
4.7
3.3
6.5
5.7
6.3
4.3
3.3
Ohio..................................................
Oklahoma ..........................................
Oregon ..............................................
Pennsylvania.....................................
Rhode Island......................................
6.4
6.0
5.5
6.2
7.1
4.5
4.9
4.6
5.8
5.8
4.7
4.6
5.2
5.7
6.4
South Carolina ...................................
South Dakota.....................................
Tennessee .........................................
Texas ................................................
Utah..................................................
6.5
3.2
4.9
6.7
3.7
4.9
3.3
4.4
5.9
3.6
4.9
2.3
4.6
6.0
3.7
Vermont ............................................
Virginia ..............................................
Washington........................................
West Virginia ......................................
4.7
4.9
6.7
8.8
4.6
4.2
4.4
6.1
7.3
3.9
3.9
4.5
6.1
7.6
3.9
Wyoming...........................................
5.3
4.4
4.8
State
p = preliminary
11.
Employment of workers on nonfarm payrolls by State, seasonally adjusted
(In thousands)
May 1994
Apr. 1995
May 1995p
California...............................................
1,746.5
258.2
1,674.2
1,027.4
12,135.5
1,774.6
261.1
1,751.3
1,070.6
12,234.4
1,770.8
261.3
1,752.6
1,069.6
12,243.6
Colorado...............................................
Connecticut ...........................................
Delaware...............................................
District of Columbia.................................
Florida ..................................................
1,742.3
1,542.5
353.8
658.9
5,765.6
1,791.2
1,545.8
360.2
647.4
5,967.4
1,787.5
1,545.7
359.7
646.6
5,985.4
Indiana ..................................................
3,242.7
534.0
460.2
5,443.0
2,707.5
3,382.5
534.6
476.7
5,541.1
2,768.0
3,384.1
533.6
474.9
5,526.8
2,762.3
1,313.7
1,159.9
1,592.2
1,705.2
530.7
1,349.8
1,190.9
1,629.0
1,788.7
542.3
1,348.7
1,195.6
1,633.8
1,794.4
541.7
2,142.7
2,888.0
4,125.7
2,304.7
1,051.0
2,456.1
2,162.4
2,951.5
4,255.2
2,361.7
1,055.8
2,545.9
2,160.4
2,948.3
4,258.8
2,361.8
1,056.3
2,535.3
State
Alaska ..................................................
Kansas ..................................................
Maine....................................................
Minnesota.............................................
Mississippi.............................................
May 1994
Apr. 1995
Nebraska..............................................
337.8
791.6
730.7
520.0
348.6
812.0
772.1
534.1
349.9
808.4
773.3
533.6
New Jersey ..........................................
New Mexico .........................................
New York..............................................
North Carolina ...................... ................
North Dakota ........................................
3,548.6
651.6
7,804.0
3,347.3
293.3
3,603.3
685.6
7,837.1
3,436.9
301.4
3,604.1
684.2
7,826.0
3,434.8
301.3
Ohio ....................................................
5,067.1
1,272.7
1,356.3
5,184.1
433.2
5,173.9
1,296.6
1,409.5
5,222.8
434.4
5,169.8
1,299.3
1,413.4
5,200.9
431.9
South Carolina......................................
1,600.6
330.6
2,411.4
7,698.7
853.3
1,626.6
341.6
2 485 8
7,975.8
898.3
1,626.8
341.3
2 487 1
7,975.1
902.7
Vermont...............................................
264.2
2,992.1
2,293.2
682.9
2,471.4
269.0
3,075.2
2,359.4
686.8
2,535.3
267.7
3,073.1
2^360.4
687.9
2,540.4
216.0
220.4
218.7
State
Wisconsin.............................................
p = preliminary
NOTE: Some data in this table may differ from data published elsewhere because of the continual updating of the database.
M onthly Labor Review
96
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
August 1995
May 1995p
12.
Employment of workers on nonfarm payrolls by industry, monthly data seasonally adjusted
(In thousands)
Annua average
1994
Industry
1993
TOTAL ........................................
PRIVATE SECTOR ......................
GOODS-PRODUCING .....................
Mining1 .............................................
Metal mining ..........................
Oil and gas extraction .............
Nonmetallic minerals, except
fuels.....................................
Construction ..................................
General building contractors.....
Heavy construction, except
building................................
Special trades contractors.......
M anufacturing................................
Production workers ...............
Durable g o o d s ..............................
Production workers ...............
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 .............................
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...............................
1994
May
June
July
Aug.
1995
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.p
Mayp
110,730 114,034 113,638 113,943 114,171 114,510 114,762 114,935 115,427 115,624 115,810 116,123 116,302 116,295 116,194
91,889 94,917 94,545 94,840 95,061 95,327 95,555 95,740 96,152 96,405 96,588 96,882 97,054 97,048 96,969
23,352
610
50
350
23,913
600
49
336
23,837
599
48
336
23,905
602
49
337
102
103
103
103
103
103
103
104
104
104
4,668
1,120
5,010
1,201
4,981
1,192
5,006
1,197
5,029
1,199
5,038
1,206
5,077
1,214
5,088
1,222
5,144
1,234
5,166
1,241
713
2,836
736
3,073
737
3,052
738
3,071
743
3,087
738
3,094
740
3,123
734
3,132
740
3,170
739
3,186
18,075
12,341
18,303
12,615
18,257
12,569
18,297
12,609
18,297
12,610
18,346
12,658
18,355
12,671
18,398
12,709
18,439
12,759
10,221
6,849
10,431
7,092
10,388
7,050
10,426
7,086
10,422
7,088
10,465
7,128
10,481
7,145
10,513
7,175
709
487
517
683
752
502
533
699
748
500
531
692
752
502
532
697
755
504
533
700
757
504
534
699
758
504
535
704
240
1,339
239
1,387
235
1,378
239
1,386
240
1,390
238
1,396
1,931
363
1,985
351
1,981
354
1,989
355
1,983
352
1,526
1,571
1,561
1,570
528
1,756
837
542
896
544
1,749
899
480
863
539
1,741
885
485
867
542
1,746
893
480
863
23,922
596
49
332
23,981
597
49
333
24,030
598
49
336
24,081
595
49
331
24,175
592
49
328
24,230
592
50
326
24,293
590
50
325
24,324
588
51
323
24,370
589
51
323
24,320
583
51
319
24,205
581
51
319
105
105
106
105
104
5,201
1,250
5,213
1,250
5,256
1,258
5,237
1,255
5,180
1,236
742
3,209
740
3,223
747
3,251
743
3,239
730
3,214
18,472
12,785
18,502
12,813
18,523
12,833
18,525
12,832
18,500
12,819
18,444
12,776
10,550
7,218
10,574
7,239
10,596
7,259
10,622
7,288
10,633
7,297
10,629
7,295
10,600
7,269
761
505
537
708
766
507
539
712
766
507
540
715
767
508
542
716
766
509
545
718
767
509
547
718
761
506
546
719
756
504
543
718
239
1,397
239
1,405
240
1,412
240
1,421
239
1,428
240
1,435
240
1,439
240
1,441
241
1 436
1,992
350
1,995
348
1,999
345
2,006
344
2,010
342
2,017
341
2,025
340
2,029
336
2,035
336
2,031
334
1,570
1,581
1,586
1,589
1,595
1,603
1,608
1,613
1,614
1,617
1,618
545
1,736
893
475
859
549
1,751
908
473
859
552
1,753
913
469
857
554
1,761
921
467
854
556
1,764
924
465
854
560
1,764
926
462
853
563
1,764
932
459
850
565
1,766
934
457
849
569
1,767
937
455
847
571
1,765
938
454
845
575
1,758
935
450
844
378
390
389
389
392
392
392
394
395
395
396
396
396
394
392
7,854
5,492
7,872
5,523
7,869
5,519
7,871
5,523
7,875
5,522
7,881
5,530
7,874
5,526
7,885
5,534
7,889
5,541
7,898
5,546
7,906
5,554
7,901
5,545
7,892
5,535
7,871
5,524
7,844
5 ,5 0 7
1,680
44
675
1,680
42
673
1,679
43
673
1,680
42
673
1,681
42
673
1,679
42
674
1,677
41
671
1,677
41
674
1,683
41
674
1,684
41
673
1,690
40
672
1,689
40
671
1,690
39
670
1,687
40
669
1,687
39
664
989
692
1,517
1,081
152
969
691
1,542
1,061
149
973
691
1,537
1,062
149
972
691
1,540
1,061
148
969
692
1,544
1,060
148
972
691
1,547
1,057
150
971
689
1,547
1,056
149
970
692
1,550
1,055
149
963
692
1,551
1,054
149
960
692
1,556
1,054
150
957
693
1,557
1,055
147
951
692
1,561
1,054
148
946
691
1,561
1,053
148
939
692
1,557
1,050
146
932
689
1 554
1,049
145
909
117
952
114
948
114
950
114
953
113
956
113
960
113
965
112
970
112
975
113
982
113
983
112
982
112
980
in
976
109
87,378
90,121
89,801
90,038
90,249
90,529
90,732
90,854
91,252
91,394
91,517
91,799
91,932
91,975
91 989
5,829
3,615
248
6,006
3,775
241
5,994
3,766
239
6,008
3,781
241
6,022
3,794
240
6,045
3,810
237
6,048
3,813
240
6,061
3,821
240
6,092
3,846
242
6,121
3,870
241
6,129
3,886
241
6,156
3,900
242
6,175
3,914
242
6,186
3,921
242
6,182
3,919
242
379
1,698
168
740
18
363
410
1,797
169
748
18
392
405
1,797
172
747
18
388
411
1,808
169
745
18
389
415
1,813
171
744
17
394
425
1,819
168
746
18
397
418
1,824
168
746
18
399
417
1,828
167
748
18
403
421
1,843
165
750
18
407
425
1,857
164
754
18
411
428
1,864
166
754
17
416
431
1,871
165
756
17
418
433
1,877
164
760
17
421
437
1,879
164
761
17
421
441
1,872
163
761
17
423
2,214
1,269
2,231
1,305
2,228
1,298
2,227
1,301
2,228
1,305
2,235
1,314
2,235
1,314
2,240
1,320
2,246
1,325
2,251
1,331
2,243
1,327
2,256
1,343
2,261
1,351
2,265
1,355
2,263
1,357
944
927
930
926
923
921
921
920
921
920
916
913
910
910
906
Wholesale trade .............................
5,981
6,140
6,118
6,131
6,138
6,163
6,181
6,195
6,210
6,229
6,251
6,275
6,287
6,301
6,292
Retail tra d e ......................................
19,773
20,437
Building materials and garden
supplies................................
General merchandise stores......
Department stores....................
Food stores.............................
20,356
20,408
20,459
20,497
20,565
20,580
20,703
20,759
20,760
20,794
20,760
20,763
20,755
779
2,488
2,140
3,224
828
2,545
2,212
3,289
825
2,532
2,198
3,289
829
2,534
2,201
3,285
833
2,542
2,211
3,292
835
2,551
2,219
3,297
838
2,555
2,225
3,296
840
2,563
2,232
3,298
844
2,598
2,268
3,308
846
2,585
2,256
3,320
851
2,562
2,236
3,325
851
2,545
2,223
3,328
849
2,530
2,207
3,332
Nondurable g o o d s .........................
Production workers.................
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....
SERVICE-PRODUCING ...................
Transportation and public
u tilities.............................................
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................................
See footnotes at end of table.
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
M onthly Labor Review
853
2,539
2,218
3,343 |
August 1995
850
2,539
2,221
3^334
97
Current Labor Statistics:
Labor Force D ata
12. Continued—Employment of workers on nonfarm payrolls by industry, monthly data seasonally adjusted
(In thousands)
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........................
Finance, insurance, and real
e s ta te ...............................................
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 ..............................
Services ..........................................
Agricultural services ..................
Hotels and other
lodging places.........................
Personal services .....................
Business services.....................
Services to buildings................
Personnel supply services ........
Help supply services ...............
Computer and data
processing services................
Auto repair services,
and parking ............................
Miscellaneous repair services.....
Motion pictures ........................
Amusement and recreation
services .................................
1995
1994
Annual average
Industry
1993
1994
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.p
Mayp
2,014
908
1,144
2,123
964
1,134
2,112
959
1,133
2,119
964
1,133
2,122
967
1,134
2,135
971
1,132
2,145
975
1,135
2,154
979
1,136
2,165
984
1,130
2,173
989
1,126
2,182
993
1,122
2,191
996
1,118
2,202
998
1,110
2,206
1,000
1,104
2,207
1,001
1,094
828
6,821
890
7,069
877
7,045
883
7,067
893
7,076
899
7,084
906
7,103
915
7,086
926
7,134
927
7,182
933
7,188
936
7,221
943
7,19.1
945
7,171
944
7,181
2,476
2,560
2,543
2,558
2,567
2,564
2,587
2,588
2,598
2,600
2,597
2,604
2,603
2,602
2,606
6,757
3,238
2,089
1,497
324
455
6,933
3,323
2,075
1,492
308
499
6,935
3,328
2,075
1,488
313
507
6,946
3,332
2,075
1,489
310
506
6,947
3,332
2,076
1,492
308
502
6,948
3,329
2,074
1,492
305
499
6,942
3,324
2,072
1,492
303
494
6,935
3,320
2,072
1,496
300
490
6,937
3,319
2,071
1,498
296
485
6,931
3,317
2,070
1,498
295
481
6,927
3,312
2,067
1,497
293
478
6,929
3,312
2,066
1,497
291
475
6,938
3,313
2,066
1,499
289
475
6,919
3,303
2,062
1,493
288
472
6,916
3,307
2,061
1,491
289
476
472
518
516
520
522
524
525
525
528
530
530
532
532
528
528
223
2,197
1,529
231
2,237
1,551
230
2,239
1,555
231
2,240
1,554
232
2,238
1,551
232
2,238
1,549
233
2,236
1,546
233
2,236
1,544
235
2,236
1,542
236
2,232
1,537
237
2,233
1,535
239
2,233
1,534
240
2,238
1,536
241
2,238
1,536
242
2,233
1,533
668
1,322
686
1,373
684
1,368
686
1,374
687
1,377
689
1,381
690
1,382
692
1,379
694
1,382
695
1,382
698
1,382
699
1,384
702
1,387
702
1,378
700
1,376
30,197
519
31,488
565
31,305
560
31,442
563
31,573
567
31,693
571
31,789
574
31,888
578
32,035
584
32,135
588
32,228
575
32,404
580
32,524
584
32,559
589
32,619
567
1,596
1,137
5,735
823
1,906
1.669
1,618
1,139
6,239
855
2,254
2,002
1,621
1,135
6,158
848
2,209
1,960
1,625
1,135
6,219
854
2,250
1,997
1,625
1,135
6,274
858
2,281
2,026
1,620
1,139
6,314
860
2,296
2,040
1,617
1,139
6,358
861
2,321
2,061
1,612
1,140
6,392
861
2,337
2,077
1,605
1,140
6,457
869
2,373
2,107
1,612
1,138
6,487
870
2,386
2,118
1,614
1,148
6,513
868
2,408
2,138
1,614
1,160
6,555
870
2,427
2.152
1,616
1,158
6,570
871
2,399
2,138
1,609
1,157
6,539
865
2,372
2,102
1,613
1,144
6,568
865
2,377
2,103
893
950
938
945
949
958
967
974
984
991
994
1,006
1,017
1,025
1,036
925
349
412
971
334
471
961
333
453
968
333
461
971
333
470
979
334
481
984
334
491
989
335
505
995
337
519
1,000
338
529
1,006
340
545
1,010
342
566
1,014
344
577
1,016
342
598
1,016
341
623
1,258
1,344
1,343
1,355
1,361
1,365
1,354
1,364
1,371
1,375
1,380
1,398
1,434
1,453
1,457
9,055
9,074
9,096
9,121
9,141
9,168
9,197
9,211
9,221
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................................
8,756
9,001
8,970
8,991
9,011
9,037
1,506
1,541
1,535
1,538
1,541
1,549
1,548
1,553
1,557
1,562
1,563
1,570
1,576
1,579
1,580
1,585
3,779
469
924
1,711
2,070
473
567
1,649
3,774
555
927
1,822
2,181
502
602
1,644
3,770
548
926
1,819
2,163
497
597
1,649
3,769
554
923
1,821
2,178
501
600
1,654
3,772
560
925
1,826
2,191
506
603
1,657
3,776
566
927
1,831
2,205
518
606
1,659
3,779
572
928
1,840
2,211
509
610
1,661
3,781
575
928
1,843
2,216
510
613
1,663
3,785
579
930
1,851
2,226
512
617
1,667
3,790
588
930
1,854
2,233
512
620
1,672
3,792
591
931
1,843
2,244
514
623
1,676
3,796
596
932
1,864
2,254
517
626
1,679
3,802
599
933
1,863
2,264
519
629
1,681
3,810
597
932
1,866
2,263
518
631
1,679
3,811
601
930
1,880
2,271
521
633
76
2,035
79
2,059
79
2,059
79
2,060
79
2,058
80
2,060
79
2,065
79
2,066
80
2,066
80
2,062
80
2,062
81
2,060
81
2,059
81
2,056
81
2,056
2,521
2,567
2,554
2,560
2,575
2,578
2,589
2,595
2,606
2,616
2,634
2,648
2,658
2,675
2,678
757
775
770
773
778
780
785
785
787
790
793
795
795
799
798
688
716
709
711
716
719
725
731
737
742
752
762
773
785
792
Government ....................................
18,841
2,915
2,128
4,488
1,834
19,118
2,870
2,053
4,562
1,875
19,093
2,873
2,062
4,548
1,867
19,103
2,866
2,051
4,553
1,868
19,110
2,864
2,045
4,572
1,882
19,183
2,861
2,041
4,594
1,900
19,207
2,863
2,039
4,589
1,891
19,195
2,858
2,031
4,589
1,888
19,275
2,854
2,022
4,596
1,892
19,219
2,853
2,014
4,598
1,891
19,222
2,838
2,004
4,599
1,889
19,241
2,831
1,997
4,610
1,901
19,248
2,828
1,992
4,613
1,904
19,247
2,808
1,969
4,607
1,906
19,225
2,802
1,961
4,602
1,911
2,654
11,438
6,353
2,687
11,685
6,490
2,681
11,672
6,465
2,685
11,684
6,480
2,690
11,674
6,497
2,694
11,728
6,548
2,698
11,755
6,554
2,701
11,748
6,544
2,704
11,825
6,549
2,707
11,768
6,557
2,710
11,785
6,577
2,709
11,800
6,591
2,709
11,807
6,599
2,701
11,832
6,617
2,691
11,821
6,619
5,085
5,195
5,207
5,204
5,177
5,180
5,201
5,204
5,276
5,211
5,208
5,209
5,208
5,215
5,202
Federal....................................
Federal, except Postal Service ...
State ......................................
Education ..............................
Other State
government...........................
Local......................................
Education ..............................
Other local
government...........................
' Includes other industries not shown separately.
p = preliminary
NOTE: See notes on the data for a description of the most recent benchmark revision.
M onthly Labor Review
Digitized for98
FRASER
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
August 1995
13. Average weekly hours of production or nonsupervisory workers on private nonfarm payrolls by industry, monthly
data seasonally adjusted
Industry
Annual
average
1993
1994
1994
May
June
July
Aug.
1995
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.»
May»
34.5
34.7
34.7
34.7
34.7
34.6
34.7
34.9
34.6
34.7
34.8
34.6
34.6
34.6
34.3
40.9
41.4
41.4
41.4
41.4
41.4
41.4
41.4
41.4
41.5
41.6
41.4
41.3
40.7
40.7
M IN IN G .......................................................................
44.3
44.7
44.6
44.9
45.4
44.6
44.9
44.8
44.9
44.7
44.9
44.9
44.6
44.6
44.3
M ANUFACTURING.................................................
41.4
4.1
42.0
4.7
42.0
4.6
42.0
4.7
42.0
4.7
42.0
4.7
42.1
4.8
42.1
4.7
42.1
4.8
42.1
4.8
42.2
4.9
42.1
4.8
42.0
4.7
41.5
4.5
41.5
4.3
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...........................
42.1
4.3
40.8
40.1
42.7
43.7
44.1
42.1
42.8
5.0
41.2
40.4
43.4
44.7
44.9
42.9
42.9
5.0
41.3
40.4
43.5
44.7
44.8
42.8
42.8
5.0
41.4
40.7
43.5
44.5
44.5
42.7
42.7
5.0
41.2
40.5
43.5
44.6
44.8
42.7
42.9
5.0
41.2
40.5
43.4
44.7
45.1
42.9
42.9
5.1
41.0
40.7
43.6
44.9
45.3
42.9
42.9
5.0
41.3
40.7
43.5
44.9
45.5
42.9
43.0
5.1
41.1
40.6
43.5
45.0
45.6
43.0
43.0
5.1
41.2
40.4
43.5
45.0
45.6
43.0
43.0
5.3
41.2
40.8
43.6
44.8
45.7
43.2
43.0
5.2
40.9
40.5
43.3
44.8
45.4
43.1
42.8
5.1
40.7
39.8
43.4
44.5
45.1
42.8
42.3
4.9
40.5
38.7
42.5
43.3
45.0
42.0
42.2
46
40.4
39 1
42.6
44.0
44.3
42.2
Industrial machinery and equipment..............
Electronic and other electrical equipment......
Transportation equipment............................
Motor vehicles and equipment ...................
Instruments and related products.................
Miscellaneous manufacturing .......................
43.0
41.8
43.0
44.3
41.1
39.8
43.7
42.2
44.3
46.0
41.7
40.0
43.7
42.2
44.3
45.8
41.7
40.2
43.8
42.2
44.1
45.5
41.6
40.2
43.6
42.2
43.6
44.8
41.9
40.2
43.6
42.2
44.4
45.9
41.8
40.0
43.8
42.0
44.3
45.9
41.8
39.9
43.7
42.2
44.4
45.8
41.9
40.1
43.8
42.1
44.7
46.4
41.8
40.0
43.8
42.0
44.7
46.2
41.7
39.9
44.0
42.1
44.6
46.1
41.8
40.1
44.0
41.9
44.7
46.1
41.7
40.2
43.9
41.8
44.5
45.8
41.7
39.9
43.2
41.5
44.5
43.4
41.4
40.1
43 5
41.3
43.5
44 1
41 4
39.9
Nondurable goods ..............................................
Overtime hours .....................................
Food and kindred products .........................
Textile mill products....................................
Apparel and other textile products ...............
Paper and allied products...........................
40.6
4.0
40.7
41.4
37.2
43.6
40.9
4.3
41.3
41.6
37.5
43.9
40.9
4.2
41.0
41.7
37.7
43.9
41.0
4.3
41.2
41.8
37.7
44.0
41.1
4.3
41.6
41.7
37.6
44.2
40.9
4.2
41.3
41.6
37.6
44.1
41.0
4.3
41.4
41.6
37.6
43.9
41.0
4.3
41.3
41.8
37.7
44.0
41.0
4.3
41.5
41.5
37.6
43.9
41.1
4.3
41.5
41.6
37.7
44.0
41.0
4.4
41.5
41.8
37.5
44.0
41.0
4.3
41.3
41.9
37.7
43.9
40.9
4.2
41.3
41.8
37.6
43.7
40.4
4.0
40.7
41.0
36.9
43.1
40.5
40
41.1
40.4
37.0
43.1
Printing and publishing ................................
Chemicals and allied products.....................
Rubber and miscellaneous plastics products ...
Leather and leather products.......................
38.3
43.1
41.8
38.6
38.6
43.2
42.2
38.6
38.8
43.3
42.2
38.5
38.7
43.2
42.2
38.4
38.6
43.3
42.3
38.0
38.6
43.2
42.2
C8.6
38.6
43.2
42.3
38.6
38.7
43.4
42.3
39.0
38.6
43.4
42.3
38.7
38.7
43.2
42.3
38.6
38.5
43.3
42.3
38.0
38.5
43.4
42.3
38.4
38.4
43.4
42.0
38.4
38 3
43 4
41.1
38.1
38.4
42 9
41 8
38.7
SERVICE-PRODUCING............................................
32.7
32.8
32.9
32.8
32.8
32.7
32 8
33.0
32.7
32.8
32.9
32.7
32.7
32.9
32.5
TRANSPORTATION AND PUBLIC UTILITIES
39.6
39.9
39.9
39.9
39.9
39.7
40.0
40.0
39.8
39.6
39.8
39.7
39.5
39.7
39.4
WHOLESALE TRADE
38.2
38.4
38.4
38.4
38.3
38.2
38.4
38.6
38.4
38.4
38.4
38.4
38.2
38.3
37.9
RETAIL T R A D E ......................................................
28.8
28.9
28.9
29.0
29.0
28.9
28.9
29.2
28.9
28.9
29.0
28.8
28.8
29.1
28.7
PRIVATE SECTOR ..................................
GOODS-PRODUCING .............
Overtime hours .....................................
Durable g o o d s .......................................................
» = preliminary
NOTE: See “Notes on the data" for a description of the most recent benchmark adjustment.
14. Average hourly earnings of production or nonsupervisory workers on private nonfarm payrolls by industry
seasonally adjusted
Industry
An lual
average
1993
PRIVATE SECTOR (in current dollars) .......
1994
1994
May
June
July
Aug.
Sept.
1995
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.»
May»
$10.83 $11.13 $11.08 $11.09 $11.13 $11.14 $11.18 $11.25 $11.24 $11.27 $11.29 $11.32 $11.34 $11.40 $11.38
GOODS-PRODUCING ...........................................
12.37
12.71
12.65
12.68
12.72
12.74
12.78
12.81
12.83
12.83
12.84
12.89
12.91
12.94
Mining .......................................................
Construction..............................................
Manufacturing ...........................................
Excluding overtime....................................
14.60
14.38
11.74
11.18
14.89
14.72
12.06
11.42
14.81
14.65
12.00
11.38
14.78 14.84
14.70 14.76
12.03 12.06
11.40 11.42
14.85
14.74
12.09
11.44
14.95
14,82
12.12
11.47
15.04
14.90
12.14
11.49
15.04
14.84
12.17
11.52
15.08
14.81
12.18
11.53
15.08
14.74
12.21
11.56
15.12
14.88
12.24
11.60
15.15
14,90
12.25
11.61
15.15 15.21
14.95 15.01
12.28 12.27
11.72 11.65
SERVICE-PRODUCING.........................................
10.30
13.62
10.57
13.86
10.53 10.54
13.79 13.79
10.57
13.84
10.57
13.87
10.62
13.88
10.70
13.99
10.68
14.02
10.71
14.01
10.74
14.03
10.76
14.00
10.79
14.05
10.87
14.14
10.84
14.07
Wholesale trade......................................... 11.74
Retail trade ............................................... 7.29
Finance, insurance, and real estate.............. 11.35
Services.................................................... 10.78
12.05
7.49
11.83
11.05
12.01
7.47
11.80
11.01
12.03
7.48
11.77
11.02
12.06
7.50
11.82
11.06
12.05
7.51
11.81
11.06
12.08
7.53
11.90
11.11
12.22 12.15 12.20
7.56 7.56 7.60
12.05 11.99 12.01
11.20 11.17 11.21
12.23
7.59
12.06
11.26
12.24
7.60
12.09
11.28
12.27
7.61
12.16
11.30
12.41
7.63
12.28
11.39
12.31
7.68
12.20
11.36
7.39
7.41
7.41
7.39
7.39
7.37
7.38
7.39
7.39
7.38
7.40
Transportation and public utilities .................
PRIVATE SECTOR (in constant (1982) dollars)
- uata not available.
= Preliminary
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
7.42
7.40
7.40
12.94
-
NOTE: See "Notes on the data” for a description of the most recent
benchmark revision.
M onthly Labor Review
August 1995
99
Current Labor Statistics:
Labor Force D ata
15. Average hourly earnings of production or nonsupervisory workers on private nonfarm payrolls by
industry
Annual
average
Industry
1993
1994
1995
1994
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.p Mayp
PRIVATE S E C TO R .....................................................
$10.83 $11.13 $11.09 $11.03 $11.05 $11.05 $11.22 $11.28 $11.27 $11.28 $11.36 $11.36 $11.36 $11.41 $11.39
M IN IN G .........................................................................
14.60
14.89
14.83
14.74
14.73
14.69
14.92
14.91
14.97
15.09
15.25
15.26
15.24
15.29
15.24
14.97
15.05
14.87
14.83
14.67
14.82
14.84
14.88
14.98
12.14
12.10
12.17
12.26
12.23
12.24
12.25
12.29
12.27
12.83 12.80
9.95 9.98
9.67 9.76
12.25 12.43
14.41 14.78
17.03 17.67
12.05 12.02
12.80
10.03
9.72
12.31
14.48
17.23
12.05
CO NSTRUCTIO N........................................................
14.38
14.72
14.62
14.59
14.75
14.79
M ANUFACTURING.....................................................
11.74
12.06
12.01
12.03
12.04
12.01
Durable goods ........................................................... 12.33 12.67 12.62 12.63 12.62 12.62 12.76 12.70 12.77 12.87 12.81 12.83
9.84 9.80 9.84 9.87 9.87 9.95 9.96 9.93 9.97 9.95 9.94
Lumber and wood products............................ 9.61
Furniture and fixtures..................................... 9.27 9.55 9.45 9.48 9.54 9.56 9.69 9.70 9.67 9.76 9.67 9.66
Stone, clay, and glass products...................... 11.85 12.13 12.10 12.15 12.17 12.19 12.27 12.22 12.21 12.21 12.19 12.23
Primary metal industries ................................ 13.99 14.33 14.24 14.31 14.40 14.34 14.40 14.37 14.44 14.53 14.54 14.43
Blast furnaces and basic steel products........ 16.36 16.85 16.74 16.79 16.93 16.95 17.05 17.08 17.13 17.16 17.30 17.09
Fabricated metal products ............................. 11.69 11.93 11.89 11.90 11.86 11.87 11.99 11.92 12.03 12.09 12.04 12.03
13.04
11.57
16.71
17.27
12.55
9.71
10.98 11.25 11.19 11.21 11.28
Food and kindred products............................. 10.45 10.66 10.64 10.65 10.68
Tobacco products.......................................... 16.89 19.10 20.27 20.78 20.60
9.12
Textile mill products...................................... 8.88 9.13 9.06 9.11
Apparel and other textile products................... 7.09 7.34 7.28 7.33 7.31
13.68
13.8313.77
13.71
13.42
Paper and allied products..............................
11.20
10.59
18.91
9.12
7.36
13.80
11.31 11.30
10.64 10.65
18.89 18.71
9.20 9.19
7.44 7.43
13.96 13.89
11.35 11.42 11.44
10.81 10.85 10.85
19.46 18.64 18.71
9.35
9.26 9.31
7.45 7.47 7.53
13.92 13.98 14.01
12.99
11.50
16.48
16.98
12.47
9.66
12.95
11.48
16.41
16.92
12.37
9.60
12.95
11.53
16.42
16.93
12.43
9.60
Nondurable goods ....................................................
13.11
11.54
16.62
17.11
12.55
9.79
13.15
11.59
16.60
17.12
12.54
9.98
12.92
11.52
16.44
16.92
12.48
9.63
12.73
11.24
15.80
16.10
12.23
9.39
13.03
11.51
16.52
16.98
12.54
9.72
13.19
11.59
16.83
17.37
12.63
9.90
12.94
11.56
16.41
16.89
12.46
9.61
Industrial machinery and equipment................
Electronic and other electrical equipment ........
Transportation equipment...............................
Motor vehicles and equipment......................
Instruments and related products ...................
Miscellaneous manufacturing..........................
13.15 13.15
11.53 11.54
16.71 16.66
17.26 17.23
12.63 1,2.63
9.94 9.90
13.05
11.48
16.46
17.00
12.68
9.94
13.17
11.54
16.42
16.91
12.66
9.94
11.43 11.45 11.59 11.53
10.83 10.87 10.95 10.94
19.67 20.44 20.03 21.66
9.31
9.30 9.38 9.38
7.62 7.56
7.48 7.51
14.02 14.03 14.27 14.18
Printing and publishing...................................
Chemicals and allied products........................
Petroleum and coal products..........................
Rubber and miscellaneous plastics products....
Leather and leather products .........................
11.93
14.82
18.53
10.57
7.63
12.13
15.14
19.07
10.70
7.98
12.05
15.05
18.76
10.69
7.97
12.08
15.08
18.87
10.72
7.96
12.12
15.16
18.94
10.75
7.98
12.12
15.08
18.76
10.65
7.97
12.26
15.27
19.32
10.65
7.99
12.23
15.30
19.29
10.66
8.03
12.20
15.29
19.25
10.69
8.05
12.26
15.42
19.32
10.79
8.06
12.24
15.40
19.19
10.82
8.13
12.24
15.42
19.55
10.76
8.14
12.26
15.43
19.38
10.80
8.13
12.21
15.72
19.55
10.78
8.33
12.21
15.53
18.83
10.90
8.31
TRANSPORTATION AND PUBLIC U T ILITIE S ....
13.62
13.86
13.74
13.70
13.81
13.84
13.91
14.01
14.07
14.04
14.08
14.04
14.06
14.13
14.01
WHOLESALE T R A D E ...............................................
11.74
12.05
12.03
11.98
12.04
12.00
12.09
12.20
12.15
12.21
12.30
12.28
12.25
12.45
12.32
RETAIL TRADE ..........................................................
7.29
7.49
7.47
7.46
7.46
7.44
7.54
7.57
7.57
7.59
7.64
7.63
7.63
7.65
7.68
FINANCE, INSURANCE, AND REAL ES TA T E ....
11.35
11.83
11.84
11.67
11.72
11.73
11.85
12.02
11.98
12.05
12.17
12.19
12.21
12.32
12.25
SERVICES ...................................................................
10.78
11.05
11.01
10.90
10.90
10.90
11.11
11.20
11.22
11.29
11.39
11.38
11.36
11.40
11.36
p = preliminary
NOTE: See “Notes on the data” for a description of the most recent benchmark revision.
100
M onthly Labor Review
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Federal Reserve Bank of St. Louis
August 1995
16. Average weekly earnings of production or nonsupervisory workers on private nonfarm payrolls by industry
Annual average
1994
Industry
1993
1994
May
June
July
Aug.
Sept.
1995
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.p
Mayp
PRIVATE SECTOR
Current dollars............................................ $373.64 $386.21 $385.93 $383.84 $386.75 $386.75 $390.46 $394.80 $389.94 $392.54 $390.78 $388.51 $389.65 $391.36 $390.68
Seasonally adjusted..................................
384.48 384.82 386.21 385.44 387.95 392.63 388.90 391.07 392.89 391.67 392.36 394.44 390.33
Constant (1982) dollars ............................... 254.87 256.96 258.15 255.72 256.98 255.79 257.56 260.25 256.54 258.42 256.25 253.93 253.84 253.96
M IN IN G .........................................................................
646.78 665.58 659.94 661.83 661.38 661.05 677.37 673.93 679.64 680.56 683.20 677.54 670.56 675.82 675.13
CO NSTRUCTIO N........................................................
553.63 572.61
580.41 579.22 587.05 588.64 598.80 595.98 572.50 573.92 553.06 546.86 565.40 560.98 576.73
MANUFACTURING
Current dollars.............................................
Constant (1982) dollars.................................
486.04 506.52 504.42 507.67 500.86 504.42 514.74 511.83 517.23 525.95 513.66 510.41 510.83 496.52 509.21
331.54 337.01 337.40 338.22 332.80 333.61 339.54 337.40 340.28 346.25 336.83 333.60 332.79 322.21
Lumber and wood products............................
Furniture and fixtures.....................................
Stone, clay, and glass products......................
Primary metal industries .................................
Blast furnaces and basic steel products........
Fabricated metal products .............................
519.09
392.09
371.73
506.00
611.36
721.48
492.15
542.28
405.41
385.82
526.44
640.55
756.57
511.80
541.40
407.68
377.06
533.61
637.95
749.95
508.89
543.09
409.34
385.84
537.03
639.66
752.19
510.51
532.56
404.67
383.51
533.05
639.36
766.93
498.12
538.87
410.59
389.09
536.36
636.70
764.45
508.04
549.96
412.93
399.23
542.33
648.00
780.89
517.97
547.37
414.34
399.64
540.12
642.34
772.02
514.94
552.94
409.12
396.47
533.58
652.69
779.42
523.31
563.71
414.75
406.02
528.69
662.57
787.64
531.96
549.55
404.97
392.60
515.64
652.85
787.15
518.92
546.56
397.60
383.50
512.44
643.58
769.05
513.68
546.56
401.98
381.00
520.63
639.80
761.24
512.13
524.80
401.20
367.95
525.79
637.02
795.15
484.41
541.44
408.22
375.19
531.79
638.57
763.29
508.51
Industrial machinery and equipment................
Electronic and other electrical equipment ........
Transportation equipment...............................
Motor vehicles and equipment......................
Instruments and related products ...................
Miscellaneous manufacturing..........................
547.39
469.83
679.40
713.23
502.65
373.72
567.66
485.30
730.06
781.08
520.00
386.40
565.92
483.31
731.89
786.78
514.59
384.00
567.21
487.72
729.05
780.47
518.33
384.96
557.71
479.74
697.43
729.65
515.84
379.60
556.85
483.84
725.00
771.55
517.92
384.24
569.85
488.25
748.61
801.33
524.59
389.37
569.41
486.87
735.14
779.38
524.17
394.63
575.53
491.60
747.90
797.33
528.36
398.45
590.91
499.53
767.45
818.13
538.04
399.96
581.23
489.10
735.38
780.67
525.43
397.20
578.60
478.50
741.92
792.23
524.15
395.61
577.29
478.91
741.37
790.86
526.67
395.01
544.19
461.50
696.26
734.40
512.27
386.67
572.90
475.45
719.20
757.57
522.86
394.62
Nondurable g o o d s ....................................................
445.79
425.32
631.69
367.63
263.75
585.11
460.13
440.26
750.63
379.81
275.25
604.50
456.55
433.05
788.50
378.71
274.46
600.50
460.73
437.72
835.36
386.26
278.54
601.92
460.22
444.29
782.80
375.74
272.66
607.14
460.32
442.66
746.95
382.13
278.21
605.82
468.23
450.07
778.27
387.32
281.23
619.82
466.69
445.17
783.95
385.98
282.34
615.33
471.03
456.18
776.45
387.07
283.10
615.26
476.21
457.87
767.97
391.02
284.61
626.30
465.61
445.94
731.56
388.03
280.12
616.44
462.92
438.62
759.26
383.57
279.00
607.07
463.73
441.32
778.76
383.16
280.12
604.69
458.96
435.81
773.16
374.26
270.51
605.05
465.81
446.35
892.39
379.89
280.48
609.74
Durable goods ...........................................................
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 .........................
TRANSPORTATION AND PUBLIC
U T IL IT IE S ...................................................................
456.92 468.22 462.72 463.87 464.20 469.04 479.37 475.75 477.02 481.82 466.34 466.34 470.78 461.54 463.98
638.74 654.05 650.16 651.46 653.40 646.93 658.14 664.02 668.17 678.48 666.82 666.14 668.12 680.68 666.24
819.03 846.71 821.69 830.28 829.57 816.06 894.52 869.98 854.70 853.94 840.52 868.02 841.09 858.25 798.39
441.83 451.54 452.19 455.60 447.20 448.37 450.50 450.92 455.39 463.97 456.60 451.92 451.44 433.36 455.62
294.52 308.03 306.85 309.64 302.44 307.64 310.81 314.78 313.95 314.34 307.31 309.32 309.75 309.04 321.60
539.35 553.01
549.60 549.37 556.54 556.37 557.79 563.20 559.99 555.98 554.75 551.77 549.75 558.14 553.40
WHOLESALE T R A D E ...............................................
448.47 462.72 464.36 461.23 462.34 459.60 464.26 472.14 466.56 470.09 469.86 467.87 465.50 476.84 469.39
RETAIL TRADE ..........................................................
209.95 216.46 215.88 218.58 222.31 220.97 218.66 220.29 217.26 222.39 215.45 214.40 215.93 221.09 220.42
FINANCE, INSURANCE, AND REAL
ESTATE ....................................................................
SERVICES ...................................................................
406.33 423.51 427.42 415.45 418.40 416.42 420.68 435.12 425.29 430.19 441.77 435.18 433.46 447.22 432.43
350.35 359.13 358.93 354.25 356.43 356.43 359.96 366.24 362.41
365.80 369.04 367.57 365.79 370.50 365.79
- Data not available.
p = preliminary
NOTE: See "Notes on the data” for a description of the most recent benchmark revision.
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
M onthly Labor Review
August 1995
101
Current Labor Statistics:
17.
Labor Force D ata
Diffusion indexes of employment change, seasonally adjusted
(In percent)
Jan.
Time span
and year
Feb.
Mar.
Apr.
June
May
July
Sept.
Aug.
Nov.
Oct.
Dec.
Private nonfarm payrolls, 356 industries
Over 1-month span:
1993 ............................................................
1994 ............................................................
1995 ............................................................
57.6
60.0
60.3
61.5
63.3
61.7
51.4
65.9
57.6
58.3
62.4
49.6
61.4
58.0
44.4
55.1
63.8
“
57.7
60.5
~
56.3
61.5
“
61.4
60.7
“
59.7
61.1
”
61.1
65.3
“
60.7
61.1
”
Over 3-month span:
1993 ............................................................
1994 ............................................................
1995 ............................................................
64.0
68.8
66.4
61.2
70.9
64.9
61.8
69.8
56.6
58.8
67.1
47.5
61.4
66.0
“
61.8
66.0
”
59.3
68.4
“
61.8
68.3
62.6
67.8
“
66.7
67.3
“
65.7
68.1
“
63.6
67.4
”
Over 6-month span:
1993 ............................................................
1994 ............................................................
1995 ............................................................
63.2
71.2
65.0
63.8
70.2
58.0
62.8
70.5
”
64.2
69.5
-
60.8
69.8
"
63.9
69.1
”
64.5
70.5
”
64.7
70.9
“
66.2
69.0
67.3
69.0
"
70.8
67.4
”
70.8
67.0
”
Over 12-month span:
1993 ............................................................
1994 ............................................................
1995 ............................................................
64.9
68.4
-
63.9
70.8
-
64.0
71.9
“
65.4
70.2
“
67.0
69.5
“
67.6
69.7
“
67.6
70.4
”
67.0
70.8
“
70.2
70.4
”
69.4
70.2
”
68.8
65.9
”
69.4
“
Manufacturing payrolls, 139 industries
Over 1-month span:
1993 ............................................................
1994 ............................................................
1995 ............................................................
52.2
59.4
56.8
57.9
61.2
54.7
52.9
59.4
49.6
44.2
56.5
42.4
51.4
55.0
37.4
46.0
59.0
50.7
54.0
“
48.6
56.5
"
56.1
53.2
-
54.7
59.4
“
56.5
59.0
“
54.3
57.6
Over 3-month span:
1993 ............................................................
1994 ............................................................
1995 ............................................................
60.8
65.1
61.5
60.4
66.5
56.1
57.2
64.4
45.3
46.4
59.0
35.6
46.4
58.6
“
50.7
58.3
”
49.6
61.5
“
54.3
59.0
”
53.2
61.5
“
60.1
60.4
“
56.1
64.0
”
57.6
62.2
-
Over 6-month span:
1993 ............................................................
1994 ............................................................
1995 ............................................................
57.6
61.9
55.4
56.5
62.9
46.8
56.1
64.4
“
55.0
61.5
“
49.3
60.8
52.2
59.0
“
55.4
62.2
~
57.9
62.6
~
56.8
61.5
57.6
64.0
”
65.1
61.5
“
62.9
61.5
”
Over 12-month span:
1993 ............................................................
1994 ............................................................
1995 ............................................................
56.8
58.3
“
57.9
59.7
”
55.8
61.9
58.6
61.5
“
57.2
61.5
“
57.6
61.5
“
58.6
61.9
”
59.0
63.3
“
61.2
61.5
60.4
59.0
”
60.1
56.1
“
59.4
-
- 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 decreasing
18.
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,
Annual data: Employment status of the population
(Numbers in thousands)
Employment status
1986
Civilian noninstitutional population..................... 180,587
Civilian labor force......................................... 117,834
Labor force participation
rate..........................................................
65.3
1987
1988
1989
1990
1991
1992
1993
1994
182,753
119,865
184,613
121,669
186,393
123,869
188,049
124,787
189,765
125,303
191,576
126,982
193,550
128,040
196,814
131,056
65.6
65.9
66.5
66.4
66.0
66.3
66.2
66.6
Employed ................................................
Employment-population ratio ...................
Agriculture.........................................
Nonagricultural industries.....................
109,597
60.7
3,163
106,434
112,440
61.5
3,208
109,232
114,968
62.3
3,169
111,800
117,342
63.0
3,199
114,142
117,914
62.7
3,186
114,728
116,877
61.6
3,233
113,644
117,598
61.4
3,207
114,391
119,306
61.6
3,074
116,232
123,060
62.5
3,409
119,651
Unemployed ...........................................
Unemployment rate...............................
Not in labor force .........................................
8,237
7.0
62,752
7,425
6.2
62,888
6,701
5.5
62,944
6,528
5.3
62,523
6,874
5.5
63,262
8,426
6.7
64,462
9,384
7.4
64,593
8,734
6.8
65,509
7,996
6.1
65,758
102 M onthly Labor Review
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Federal Reserve Bank of St. Louis
August 1995
19.
Annual data: Employment levels by industry
(In thousands)
Industry
Total employment..............................
Private sector...............................................................
Goods-producing........................................................
Mining.......................................
Construction ..........................................................
Manufacturing........................................................
Service-producing..........................................
Transportation and public utilities............................
Wholesale trade ............................
Retail trade ................................
Finance, insurance, and real estate........................
Services.......................................
Government.......................................
Federal.........................................
State................................................
Local ...............................................
1986
1987
1988
1989
1990
1991
1992
1993
1994
99,344 101,958 105,210 107,895 109,419 108,256 108,604 110,730 114,034
82,651 84,948 87,824 90,117 91,115 89,854 89,959 91,889 94,917
24,533 24,674 25,125 25,254 24,905 23,745 23,231 23,352 23,913
777
717
713
692
709
689
635
610
600
4,810
4,958
5,098
5,171
5,120
4,650
4,492
4,668
5,010
18,947 18,999 19,314 19,391 19,076 18,406 18,104 18,075 18,303
74,811
5,247
5,761
17,880
6,273
22,957
77,284
5,362
5,848
18,422
6,533
24,110
80,086
5,514
6,030
19,023
6,630
25,504
82,642
5,625
6,187
19,475
6,668
26,907
84,514
5,793
6,173
19,601
6,709
27,934
84,511
5,762
6,081
19,284
6,646
28,336
85,373
5,721
5,997
19,356
6,602
29,052
87,378
5,829
5,981
19,773
6,757
30,197
90,121
6,006
6,140
20,437
6,933
31,488
16,693
2,899
3,893
9,901
17,010
2,943
3,967
10,100
17,386
2,971
4,076
10,339
17,779
2,988
4,182
10,609
18,304
3,085
4,305
10,914
18,402
2,966
4,355
11,081
18,645
2,969
4,408
11,267
18,841
2,915
4,488
11,438
19,118
2,870
4,562
11,685
NOTE: See “Notes on the data” for a description of the most recent benchmark revision.
20. Annual data: Average hours and earnings of production or nonsupervisory workers on nonfarm
payrolls, by industry
Industry
1986
1987
1988
1989
1990
1991
1992
1993
1994
34.8
8.76
304.85
34.8
8.98
312.50
34.7
9.28
322.02
34.6
9.66
334.24
34.5
10.01
345.35
34.3
10.32
353.98
34.4
10.57
363.61
34.5
10.83
373.64
34.7
11.13
386.21
42.2
12.46
525.81
42.4
12.54
531.70
42.3
12.80
541.44
43.0
13.26
570.18
44.1
13.68
603.29
44.4
14.19
630.04
43.9
14.54
638.31
44.3
14.60
646.78
44.7
14.89
665.58
37.4
12.48
466.75
37.8
12.71
480.44
37.9
13.08
495.73
37.9
13.54
513.17
38.2
13.77
526.01
38.1
14.00
533.40
38.0
14.15
537.70
38.5
14.38
553.63
38.9
14.72
572.61
40.7
9.73
396.01
41.0
9.91
406.31
41.1
10.19
418.81
41.0
10.48
429.68
40.8
10.83
441.86
40.7
11.18
455.03
41.0
11.46
469.86
41.4
11.74
486.04
42.0
12.06
506.52
39.2
11.70
458.64
39.2
12.03
471.58
38.8
12.26
475.69
38.9
12.60
490.14
38.9
12.97
504.53
38.7
13.22
511.61
38.9
13.45
523.21
39.6
13.62
539.35
39.9
13.86
553.01
38.3
9.34
357.72
38.1
9.59
365.38
38.1
9.98
380.24
38.0
10.39
394.82
38.1
10.79
411.10
38.1
11.15
424.82
38.2
11.39
435.10
38.2
11.74
448.47
38.4
12.05
462.72
29.2
6.03
176.08
29.2
6.12
178.70
29.1
6.31
183.62
28.9
6.53
188.72
28.8
6.75
194.40
28.6
6.94
198.48
28.8
7.12
205.06
28.8
7.29
209.95
28 9
7.49
216.46
36.4
8.36
304.30
36.3
8.73
316.90
35.9
9.06
325.25
35.8
9.53
341.17
35.8
9.97
356.93
35.7
10.39
370.92
35.8
10.82
387.36
35.8
11.35
406.33
35.8
11.83
423.51
32.5
8.18
265.85
32.5
8.49
275.93
32.6
8.88
289.49
32.6
9.38
305.79
32.5
9.83
319.48
32.4
10.23
331.45
32.5
10.54
342.55
32.5
10.78
350.35
32 5
11.05
359.13
Private sector:
Average weekly hours...........................
Average hourly earnings (in dollars).................................
Average weekly earnings (in dollars) .......................
Mining:
Average weekly hours ................................
Average hourly earnings (in dollars) ..........................
Average weekly earnings (in dollars)...........................
Construction:
Average weekly hours .......................
Average hourly earnings (in dollars) ......................
Average weekly earnings (in dollars)....................
Manufacturing:
Average weekly hours ...........................
Average hourly earnings (in dollars) ............................
Average weekly earnings (in dollars)........................
Transportation and public utilities:
Average weekly hours ..........................
Average hourly earnings (in dollars) ............................
Average weekly earnings (in dollars)...........................
Wholesale trade:
Average weekly hours ........................
Average hourly earnings (in dollars)............................
Average weekly earnings (in dollars)...........................
Retail trade:
Average weekly hours ...................
Average hourly earnings (in dollars) .........................
Average weekly earnings (in dollars).....................
Finance, insurance, and real estate:
Average weekly hours ........................
Average hourly earnings (in dollars).........................
Average weekly earnings (in dollars).................
Services:
Average weekly hours ....................
Average hourly earnings (in dollars) ....................
Average weekly earnings (in dollars).......................
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
M onthly Labor Review
August 1995
103
Current Labor Statistics:
21.
C o m pe nsatio n & Industrial Relations
Employment Cost Index, compensation,1 by occupation and industry group
(June 1989=100)
Series
Mar.
June
1995
1994
1993
Sept.
Dec.
Mar.
June
Sept.
Dec.
Mar.
Percent change
3
months
ended
12
months
ended
Mar. 995
Civilian workers 2 ..........................................................................
117.5
118.3
119.5
120.2
121.3
122.1
123.3
123.8
124.8
0.8
2.9
Workers, by occupational group:
White-collar workers...................................................
Professional specialty and technical............................
Executive, administrative, and managerial....................
Administrative support, including clerical .....................
Blue-collar workers......................................................
Service occupations....................................................
117.9
120.1
116.9
118.3
116.7
117.9
118.6
120.6
117.5
119.3
117.8
118.7
119.9
122.0
118.6
120.4
118.8
119.9
120.6
122.5
119.4
121.3
119.4
120.5
121.8
123.7
120.6
122.6
120.4
121.6
122.6
124.2
121.6
123.5
121.3
122.1
123.9
125.7
122.9
124.6
122.4
123.5
124.4
126.2
123.6
125.2
122.7
124.3
125.5
127.0
125.2
126.5
123.6
125.0
.9
.6
1.3
1.0
.7
.6
3.0
2.7
3.8
3.2
2.7
2.8
Workers, by industry division:
Goods-producing..........................................................
Manufacturing............................................................
Service-producing........................................................
Services............................................................ .......
Health services.......................................................
Hospitals..............................................................
Educational services................................................
Public administration 3................................................
Nonmanufacturing........................................................
118.0
118.6
117.2
120.1
122.3
122.0
120.1
117.6
117.1
119.1
119.7
118.0
120.6
123.2
122.6
120.2
118.0
117.9
120.0
120.6
119.3
122.2
124.4
123.9
122.6
119.3
119.2
120.6
121.3
120.0
122.9
125.4
125.0
122.9
120.0
119.8
121.9
122.5
121.0
123.8
126.1
125.9
123.2
121.5
120.9
123.0
123.5
121.7
124.2
126.6
126.4
123.6
122.2
121.7
123.9
124.4
123.1
125.8
127.8
127.5
126.0
123.7
123.0
124.4
125.1
123.6
126.4
128.5
128.4
126.4
124.2
123.4
125.3
126.2
124.6
127.2
129.4
128.8
126.9
125.4
124.4
.7
.9
.8
.6
.7
.3
.4
1.0
.8
2.8
3.0
3.0
2.7
2.6
2.3
3.0
3.2
2.9
117.1
117.5
118.0
118.5
119.1
119.5
119.8
120.2
121.0
121.4
122.0
122.3
123.0
123.4
123.5
123.9
124.5
125.0
.8
.9
2.9
3.0
117.4
118.3
120.4
116.5
112.9
118.3
119.2
121.3
117.2
113.8
119.4
120.2
122.2
118.1
115.6
120.2
121.0
122.9
118.9
116.5
121.5
122.4
124.6
120.3
117.2
122.5
123.3
125.3
121.3
118.8
123.5
124.4
126.3
122.6
119.2
124.1
125.1
126.8
123.3
119.6
125.3
126.3
127.7
124.9
120.2
1.0
1.0
.7
1.3
.5
3.1
3.2
2.5
3.8
2.6
118.1
119.2
120.3
121.2
122.5
123.5
124.5
125.1
126.5
1.1
3.3
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 ....
116.6
116.6
117.8
113.9
116.8
117.7
117.6
119.0
115.2
117.6
118.7
118.7
120.0
115.9
118.4
119.3
118.9
120.8
117.0
119.1
120.3
120.2
121.3
118.5
120.2
121.2
121.2
122.2
119.1
121.4
122.3
122.5
122.9
120.3
122.7
122.6
122.5
123.4
120.6
122.9
123.5
123.4
124.2
121.8
124.1
.7
.7
.6
1.0
1.0
2.7
2.7
2.4
2.8
3.2
Service occupations..................................................
117.2
118.0
118.9
119.5
120.6
121.0
121.8
122.9
123.4
.4
2.3
Production and nonsupervisory occupations4...............
116.9
117.9
119.0
119.7
120.7
121.6
122.6
123.1
124.1
.8
2.8
Workers, by industry division:
Goods-producing.......................................................
Excluding sales occupations.................................
White-collar occupations........................................
Excluding sales occupations.................................
Blue-collar occupations..........................................
Service occupations..............................................
Construction............................................................
Manufacturing...........................................................
White-collar occupations.......................................
Excluding sales occupations................................
Blue-collar occupations.........................................
Service occupations.............................................
Durables................................................................
Nondurables...........................................................
118.0
117.8
118.6
118.1
117.6
120.0
114.9
118.6
118.7
118.0
118.5
120.3
119.0
117.9
119.1
118.8
119.6
119.0
118.7
120.6
116.0
119.7
119.7
118.8
119.6
120.7
120.0
119.0
119.9
119.6
120.5
119.7
119.6
121.5
116.8
120.6
120.5
119.5
120.5
121.7
121.0
119.7
120.6
120.1
121.1
119.9
120.2
122.4
116.5
121.3
121.3
119.9
121.3
122.7
121.9
120.3
121.8
121.4
123.0
121.9
121.1
123.5
118.6
122.5
122.7
121.3
122.3
123.8
122.9
121.7
123.0
122.5
124.3
123.2
122.2
123.8
120.2
123.5
123.9
122.5
123.2
124.1
123.8
122.8
123.9
123.5
125.1
124.1
123.1
126.5
121.4
124.4
124.9
123.6
124.0
127.0
125.1
123.2
124.3
124.0
125.9
125.0
123.4
126.3
120.8
125.1
126.0
124.9
124.5
127.0
125.8
123.8
125.3
124.9
127.2
126.2
124.1
127.3
121.1
126.2
127.4
126.1
125.3
128.0
127.0
124.7
.8
.7
1.0
1.0
.6
.8
.2
.9
1.1
1.0
.6
.8
1.0
.7
2.9
2.9
3.4
3.5
2.5
3.1
2.1
3.0
3.8
4.0
2.5
3.4
3.3
2.5
116.4
117.3
116.9
118.4
114.3
116.8
114.8
112.8
117.4
116.5
118.6
114.7
115.4
115.3
116.0
114.5
115.9
114.1
117.3
118.3
117.8
119.3
115.5
117.7
116.0
114.1
118.3
117.5
119.4
115.9
116.2
116.4
116.8
115.6
117.2
114.7
118.5
119.3
119.0
120.4
116.6
118.6
116.8
114.8
119.2
118.5
120.2
116.4
117.0
116.6
117.6
116.2
117.1
115.5
119.3
120.2
119.8
121.4
117.2
119.1
117.5
115.7
119.9
119.2
120.8
117.1
118.0
117.8
118.7
116.8
118.3
116.3
120.4
121.4
121.0
122.7
118.4
120.2
119.2
117.1
121.7
121.0
122.7
117.6
118.6
117.9
119.3
117.5
119.6
115.3
121.2
122.1
121.9
123.4
119.1
120.7
119.8
117.7
122.6
122.1
123.2
119.4
119.8
119.7
120.3
119.2
120.6
118.0
122.3
123.3
122.9
124.6
120.6
121.3
121.4
119.7
123.6
122.9
124.4
120.5
120.9
120.6
121.3
120.4
120.3
118.7
122.8
123.8
123.4
125.1
120.7
122.5
122.1
120.3
124.4
124.0
124.8
120.6
120.9
121.5
122.0
120.1
120.0
119.3
123.9
125.0
124.6
126.4
122.1
123.0
124.0
122.3
126.1
126.3
125.9
121.7
122.4
123.2
124.4
120.9
120.8
120.1
.9
1.0
1.0
1.0
1.2
.4
1.6
1.7
1.4
1.9
.9
.9
1.2
1.4
2.0
.7
.7
.7
2.9
3.0
3.0
3.0
3.1
2.3
4.0
4.4
3.6
4.4
2.6
3.5
3.2
4.5
4.3
2.9
1.0
4.2
Private industry w o rk e rs ..........................................................
Excluding sales occupations......................................
Workers, by occupational group:
White-collar workers..................................................
Excluding sales occupations...................................
Professional specialty and technical occupations........
Executive, administrative, and managerial occupations
Sales occupations...................................................
Administrative support occupations, including
clerical.................................................................
Service-producing ......................................................
Excluding sales occupations................................
White-collar occupations.........................................
Excluding sales occupations..................................
Blue-collar occupations..........................................
Service occupations..............................................
Electric, gas, and sanitary services ........................
Excluding sales occupations.................................
General merchandise stores................................
See footnotes at end of table.
104
M onthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
August 1995
21. Continued—Employment Cost Index, compensation,' by occupation and industry group
(June 1989=100)
1993
1994
1995
Series
Mar.
June
Sept.
Dec.
Mar.
June
Sept.
Dec.
Mar.
Percent change
3
months
ended
12
months
ended
Mar. 1995
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......................................
112.6
114.9
113.1
116.4
115.7
117.5
116.4
118.2
117.7
119.7
117.7
120.3
118.5
121.5
118.9
121.8
120.2
123.7
1.1
1.6
2.1
3.3
114.6
114.3
120.1
116.5
123.0
122.7
120.5
121.5
116.0
116.1
120.9
117.4
124.0
123.4
120.6
121.5
116.9
117.4
122.3
118.1
125.0
124.5
123.8
125.0
117.8
119.7
123.1
118.6
126.0
125.6
124.1
125.3
118.7
119.4
119.9
120.5
124.4 » 124.9
121.3
122.1
126.7
127.1
126.7
127.1
124.5
125.4
125.7
126.0
120.8
121.5
125.9
122.4
127.9
127.7
128.2
128.5
120.5
122.3
126.6
123.0
128.7
128.6
128.4
128.8
123.5
123.5
127.5
124.5
129.7
128.9
128.8
129.3
2.5
1.0
.7
1.2
.8
.2
.3
.4
4.0
3.0
2.5
2.6
2.4
1.7
3.5
2.9
Nonmanufacturing ....................................................
White-collar occupations............. ..........................
Excluding sales occupations................................
Blue-collar occupations.........................................
Service occupations .............................................
116.3
117.0
118.5
114.6
116.8
117.2
117.9
119.4
115.6
117.7
118.4
119.0
120.4
116.6
118.6
119.0
119.9
121.4
117.1
119.1
120.3
121.1
122.8
118.2
120.2
121.2
122.1
123.6
119.1
120.7
122.3
123.1
124.7
120.5
121.3
122.6
123.5
125.1
120.5
122.4
123.7
124.7
126.4
121.5
123.0
.9
1.0
1.0
.8
.5
2.8
3.0
2.9
2.8
2.3
State and local government workers ..................................
119.3
119.6
121.4
121.9
122.6
123.1
125.0
125.6
126.4
.6
3.1
Workers, by occupational group:
White-collar workers..................................................
Professional specialty and technical.........................
Executive, administrative, and managerial.................
Administrative support, including clerical...................
Blue-collar workers...................................................
119.5
119.6
119.0
119.2
118.3
119.6
119.7
119.2
119.6
118.7
121.5
121.7
121.0
121.0
120.5
121.9
122.0
121.6
121.6
121.4
122.6
122.5
122.8
122.7
122.3
122.9
122.7
123.4
123.3
122.7
124.9
125.0
124.7
124.9
124.2
125.5
125.5
125.3
125.6
124.7
126.2
126.0
126.9
126.3
125.4
.6
.4
1.3
.6
.6
2.9
2.9
3.3
2.9
2.5
Workers, by industry division:
Services..................................................................
Services excluding schools5....................................
Health services....................................................
Hospitals...........................................................
Educational services.............................................
Schools............................................................
Elementary and secondary ...............................
Colleges and universities..................................
Public administration3................................................
120.0
119.6
120.2
120.0
120.0
120.2
120.7
118.4
117.6
120.2
120.0
120.7
120.4
120.1
120.3
120.8
118.5
118.0
122.2
121.4
122.2
122.0
122.3
122.5
123.0
120.8
119.3
122.6
121.9
123.1
123.3
122.7
122.9
123.6
120.7
120.0
123.1
122.8
124.2
123.7
122.9
123.2
123.7
121.5
121.5
123.4
123.3
125.2
124.5
123.1
123.4
123.8
122.0
122.2
125.6
124.9
127.2
127.0
125.5
125.9
126.3
124.5
123.7
126.1
125.6
127.7
127.7
126.0
126.3
126.5
125.5
124.2
126.7
126.4
128.4
128.4
126.5
126.8
127.1
126.0
125.4
.5
.6
.5
.5
.4
.4
.5
.4
1.0
2.9
2.9
3.4
3.8
2.9
2.9
2.7
3.7
3.2
1 Cost (cents per hour worked) measured in the Employment Cost Index
consists of wages, salaries, and employer cost of employee benefits.
2 Consist of private industry workers (excluding farm and household workers)
and State and local government (excluding Federal Government) workers.
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
3 Consist 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.
M onthly Labor Review
August 1995
105
Current Labor Statistics:
22.
C o m pe nsatio n & Industrial Relations
Employment Cost Index, wages and salaries, by occupation and industry group
(June 1989=100)
Series
Mar.
June
1995
1994
1993
Sept.
Dec.
Mar.
June
Sept.
Dec.
Mar.
Percent change
3
months
ended
12
months
ended
Mar. 1995
Civilian workers 1 ..........................................................................
114.5
115.2
116.4
117.1
117.8
118.6
119.8
120.4
121.3
0.7
3.0
Workers, by occupational group:
White-collar workers...................................................
Professional specialty and technical..................... ......
Executive, administrative, and managerial...................
Administrative support, including clerical .....................
Blue-collar workers......................................................
Service occupations....................................................
115.4
117.5
115.0
115.3
112.7
114.5
116.0
118.0
115.5
116.1
113.4
115.2
117.4
119.5
116.5
117.1
114.4
116.1
118.1
120.0
117.3
118.0
115.0
116.6
118.8
120.7
118.1
118.9
115.8
117.5
119.7
121.3
119.0
119.8
116.7
118.1
120.8
122.8
120.2
120.9
117.8
119.4
121.5
123.5
120.8
121.6
118.2
120.4
122.4
124.2
122.2
122.8
119.2
121.2
.7
.6
1.2
1.0
.8
.7
3.0
2.9
3.5
3.3
2.9
3.1
Workers, by industry division:
Goods-producing..........................................................
Manufacturing............................................................
Service-producing........................................................
Services..................................................................
Health services......................................................
Hospitals............................................................
Educational services ..............................................
Public administration 2 ..............................................
Nonmanufacturing.......................................................
113.8
114.7
114.8
117.4
119.5
118.9
117.9
114.4
114.4
114.6
115.5
115.5
117.8
120.3
119.5
118.0
114.9
115.1
115.4
116.3
116.8
119.5
121.4
120.7
120.4
115.9
116.4
116.2
117.3
117.5
120.0
122.2
121.7
120.7
116.6
117.0
117.0
118.0
118.2
120.9
122.8
122.4
121.0
117.9
117.7
118.0
119.0
118.9
121.3
123.4
123.0
121.3
118.5
118.5
119.0
120.0
120.2
122.8
124.4
124.0
123.8
119.9
119.7
119.6
120.8
120.7
123.5
125.4
124.9
124.3
120.6
120.2
120.5
121.9
121.7
124.4
126.1
125.5
125.0
121.9
121.1
.8
.9
.8
.7
.6
.5
.6
1.1
.7
3.0
3.3
3.0
2.9
2.7
2.5
3.3
3.4
2.9
113.9
114.2
114.6
115.0
115.7
115.9
116.4
116.6
117.2
117.5
118.1
118.3
119.1
119.4
119.7
120.0
120.6
121.0
.8
.8
2.9
3.0
114.7
115.7
117.1
115.5
116.4
117.9
116.7
117.4
118.9
117.5
118.2
119.5
118.3
119.0
120.4
119.3
119.9
121.3
120.2
121.0
122.2
120.8
121.7
123.0
121.7
122.8
123.7
.7
.9
.6
2.9
3.2
2.7
114.7
110.5
115.3
111.6
116.2
113.8
117.0
114.7
117.8
114.8
118.8
116.2
120.0
116.5
120.5
116.7
121.9
116.9
1.2
.2
3.5
1.8
115.2
116.1
117.1
118.0
119.0
119.9
120.9
121.6
122.9
1.1
3.3
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.............................................................
112.5
113.2
114.1
114.8
115.6
116.5
117.5
118.0
119.0
.8
2.9
112.4
113.2
110.0
113.2
113.8
111.2
114.2
114.7
111.7
114.7
115.6
112.6
115.5
116.2
113.5
116.5
117.2
114.0
117.8
118.0
115.2
117.9
118.8
115.6
118.8
119.6
117.0
.8
.7
1.2
2.9
2.9
3.1
113.6
114.3
114.9
115.7
116.6
117.3
117.9
118.9
120.1
1.0
3.0
Service occupations...............................................
113.5
114.1
114.9
115.3
116.3
116.8
117.6
118.8
119.4
.5
2.7
Production and nonsupervisory occupations3.............
113.4
114.2
115.3
115.9
116.6
117.5
118.5
119.1
119.9
.7
2.8
Workers, by industry division:
Goods-producing.....................................................
Excluding sales occupations................................
White-collar occupations........................................
Excluding sales occupations.................................
Blue-collar occupations .........................................
Service occupations..............................................
113.8
113.5
115.4
114.9
112.8
113.9
114.5
114.2
116.4
115.6
113.4
114.4
115.3
114.9
117.3
116.4
114.1
115.7
116.1
115.6
118.2
116.8
114.9
116.9
116.9
116.4
119.1
117.7
115.6
116.4
118.0
117.4
120.3
118.8
116.6
117.7
118.9
118.4
121.1
119.8
117.5
120.1
119.6
119.1
122.0
120.8
118.1
119.7
120.4
119.9
123.0
121.8
118.8
120.6
.7
.7
.8
.8
.6
.8
3.0
3.0
3.3
3.5
2.8
3.6
Construction ..........................................................
109.5
110.4
111.3
111.1
112.2
113.6
114.6
114.7
114.8
.1
2.3
121.9
123.9
122.4
120.4
121.5
121.9
121.9
.9
1.0
.8
.8
.7
.9
.9
3.3
3.7
3.7
3.0
4.0
3.5
3.0
Private industry w o rk e rs .......................................................
Excluding sales occupations....................................
Workers, by occupational group:
White-collar workers...............................................
Excluding sales occupations................................
Professional specialty and technical occupations.....
Executive, administrative, and managerial
occupations.......................................................
Sales occupations................................................
Administrative support occupations, including
clerical...............................................................
Manufacturing........................................................
White-collar occupations.....................................
Excluding sales occupations.............................
Blue-collar occupations......................................
Service occupations...........................................
Durables.............................................................
Nondurables........................................................
114.7
116.0
115.3
113.9
114.3
114.4
115.5
115.5
116.9
115.9
114.5
114.5
115.1
116.3
116.3
117.7
116.7
115.2
116.0
115.9
116.9
117.3
118.8
117.2
116.2
117.3
117.2
117.5
118.0
119.5
118.0
116.9
116.8
117.8
118.3
119.0
120.6
119.1
117.8
118.2
118.7
119.5
120.0
121.7
120.2
118.7
120.6
119.8
120.3
120.8
122.7
121.4
119.5
120.6
120.8
120.8
Service-producing....................................................
Excluding sales occupations................................
White-collar occupations........................................
Excluding sales occupations..............................
Blue-collar occupations..........................................
Service occupations..............................................
113.9
114.8
114.5
116.0
111.9
113.5
114.7
115.6
115.2
116.8
112.9
114.1
115.9
116.6
116.5
117.8
114.1
114.9
116.6
117.4
117.3
118.7
114.6
115.2
117.3
118.3
118.0
119.6
115.5
116.3
118.2
119.0
118.9
120.4
116.2
116.7
119.2
120.2
119.9
121.5
117.5
117.3
119.7
120.7
120.4
122.1
117.6
118.7
120.7
121.8
121.3
123.2
119.2
119.3
.8
.9
.7
.9
1.4
.5
2.9
3.0
2.8
3.0
3.2
2.6
Transportation and public utilities...........................
Transportation....................................................
Public utilities......................................................
Communications...............................................
Electric, gas, and sanitary services.....................
112.9
110.8
115.4
114.7
116.3
114.0
112.0
116.4
115.6
117.4
114.7
112.6
117.2
116.5
118.2
115.4
113.4
117.9
117.1
118.8
116.4
114.2
119.1
118.4
119.9
117.2
114.8
120.1
119.5
120.9
118.9
116.7
121.4
121.0
121.9
119.6
117.5
122.3
122.1
122.4
121.2
119.0
123.9
124.3
123.4
1.3
1.3
1.3
1.8
.8
4.1
4.2
4.0
5.0
2.9
See footnotes at end of table.
106
M onthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
August 1995
22. Continued— Employment Cost Index, wages and salaries, by occupation and industry group
(June 1989=100)
1993
1994
1995
Percent change
3
months
ended
Series
Mar.
June
Sept.
Dec.
Mar.
June
Sept.
Mar.
Dec.
12
months
ended
Mar. 1995
Wholesale and retail trade.....................................
Excluding sales occupations.............................
Wholesale trade ................................................
Excluding sales occupations............................
Retail trade.......................................................
Food stores....................................................
Général merchandise stores.............................
113.0
113.6
113.9
114.7
112.6
114.6
112.4
114.2
114.4
115.1
115.5
113.8
115.4
113.4
114.7
115.2
115.1
116.3
114.5
114.9
114.5
115.4
116.1
116.4
117.5
115.0
115.9
115.0
115.5
116.5
116.2
117.8
115.2
117.0
114.0
117.4
117.8
118.3
118.8
117.0
117.8
116.4
118.3
118.7
118.9
119.6
118.0
117.4
116.5
118.4
118.8
119.9
120.2
117.8
117.3
117.5
119.4
120.2
120.9
122.2
118.7
117.8
117.9
0.8
1.2
.8
1.7
.8
.4
.3
3.4
3.2
4.0
3.7
3.0
.7
3.4
Finance, insurance, and real estate.......................
Excluding sales occupations ............................
Banking, savings and loan, and other
credit agencies................................................
Insurance..........................................................
109.3
112.0
109.3
113.1
112.3
114.0
112.9
114.6
113.7
115.5
113.2
116.0
113.8
117.2
114.2
117.4
115.0
119.3
.7
1.6
1.1
3.3
112.1
111.2
112.9
112.9
113.7
113.9
114.5
116.6
114.7
116.0
115.0
116.8
116.5
117.7
116.2
118.6
119.2
119.8
2.6
1.0
3.9
3.3
Services..............................................................
Business services...............................................
Health services...................................................
Hospitals .........................................................
Educational services ...........................................
Colleges and universities...................................
117.0
114.2
119.8
119.3
117.5
118.0
117.6
114.6
120.7
119.9
117.4
117.7
118.9
115.3
121.7
121.0
120.7
121.3
119.6
115.7
122.6
122.0
120.9
121.6
120.8
118.8
123.1
122.8
121.2
122.0
121.3
119.4
123.5
123.3
122.2
122.2
122.2
119.9
124.3
123.9
124.9
124.5
123.0
120.4
125.4
124.8
125.1
124.9
123.9
122.1
126.2
125.4
125.6
125.5
.7
1.4
.6
.5
.4
.5
2.6
2.8
2.5
2.1
3.6
2.9
Nonmanufacturing..................................................
White-collar occupations.......................................
Excluding sales occupations................................
Blue-collar occupations.........................................
Service occupations .............................................
113.4
114.4
115.8
111.1
113.4
114.2
115.2
116.6
111.9
114.1
115.4
116.4
117.6
113.0
114.8
116.0
117.2
118.5
113.4
115.1
116.8
117.9
119.4
114.2
116.3
117.7
118.9
120.2
115.1
116.7
118.7
119.7
121.3
116.4
117.3
119.1
120.2
121.8
116.4
118.6
120.0
121.1
122.9
117.5
119.2
.8
.7
.9
.9
.5
2.7
2.7
2.9
2.9
2.5
State and local government workers.........................
117.2
117.4
119.3
119.7
120.4
120.7
122.8
123.4
124.3
.7
3.2
Workers, by occupational group:
White-collar workers...............................................
Professional specialty and technical.......................
Executive, administrative, and managerial...............
Administrative support, including clerical.................
Blue-collar workers.................................................
117.5
118.1
116.5
115.4
116.2
117.6
118.2
116.6
115.9
116.5
119.6
120.4
118.2
117.2
118.4
119.9
120.7
118.8
117.8
119.0
120.6
121.1
119.8
118.9
119.7
120.9
121.3
120.3
119.4
120.1
122.9
123.6
121.6
120.9
121.8
123.6
124.2
122.4
121.7
122.5
124.4
124.8
124.1
122.5
123.1
.6
.5
1.4
.7
.5
3.2
3.1
3.6
3.0
2.8
Workers, by industry division:
Services ...............................................................
Services excluding schools4..................................
Health services..................................................
Hospitals........................................................
Educational services.............................................
Schools............................................................
Elementary and secondary ...............................
Colleges and universities..................................
Public administration 2.............................................
118.1
118.4
118.1
117.6
118.0
117.9
118.7
115.5
114.4
118.2
118.7
118.8
118.2
118.1
118.0
118.8
115.6
114.9
120.3
120.1
120.4
119.9
120.3
120.3
121.1
117.8
115.9
120.6
120.4
121.0
120.7
120.6
120.7
121.6
117.7
116.6
121.1
121.3
121.9
121.2
120.9
121.0
121.7
118.6
117.9
121.3
121.9
122.9
122.0
121.1
121.2
121.8
119.2
118.5
123.6
123.2
124.7
124.2
123.6
123.8
124.5
121.5
119.9
124.2
124.0
125.3
125.1
124.2
124.3
124.9
122.5
120.6
124.9
125.0
126.0
125.8
124.8
125.0
125.5
123.2
121.9
.6
.8
.6
.6
.5
.6
.5
.6
1.1
3.1
3.1
3.4
3.8
3.2
3.3
3.1
3.9
3.4
1 Consists of private industry workers (excluding farm and household workers)
and State and local government (excluding Federal Government) workers.
2 Consists of legislative, judicial, administrative, and regulatory activities.
23.
3 This series has the same industry and occupational coverage as the Hourly
Earnings Index, which was discontinued in January 1989.
4 Includes, for example, library, social and health services.
Employment Cost Index, benefits, private industry workers by occupation and industry group
(June 1989 = 100)
1993
1994
1995
Percent change
3
months
ended
Series
Mar.
June
Sept.
Dec.
Mar.
June
Sept.
Dec.
Mar.
12
months
ended
Mar. 1995
Private industry workers ...............................................
125.2
126.7
127.7
128.3
130.7
131.7
132.8
133.0
134.5
1.1
2.9
Workers, by occupational group:
White-collar workers ...................................................
Blue-collar workers......................................................
124.7
125.5
125.9
127.3
126.8
128.4
127.6
128.9
130.5
130.5
131.6
131.5
132.8
132.7
133.3
132.5
135.2
133.3
1.4
.6
3.6
2.1
Workers, by industry group:
Goods-producing........................................................
Service-producing.......................................................
Manufacturing ............................................................
Nonmanufacturing......................................................
127.3
123.4
126.8
124.2
129.0
124.6
128.6
125.5
130.0
125.7
129.7
126.5
130.3
126.7
130.0
127.4
132.7
128.9
132.0
129.9
133.9
129.7
133.0
130.8
134.8
131.2
133.9
132.2
134.8
131.5
134.3
132.3
135.9
133.2
135.4
133.9
.8
1.3
.8
1.2
2.4
3.3
2.6
3.1
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
M onthly Labor Review
August 1995
107
Current Labor Statistics:
24.
C o m pe nsatio n & Industrial Relations
Employment Cost Index, private nonfarm workers, by bargaining status, region, and area size
(June 1989=100)
1993
1994
1995
Series
Mar.
June
Sept.
Dec.
Mar.
June
Sept.
Dec.
Mar.
Percent change
3
months
ended
12
months
ended
Mar. 1995
COMPENSATION
Workers, by bargaining status’
Union ..........................................................................
Goods-producing........................................................
Service-producing.......................................................
Manufacturing ............................................................
Nonmanufacturing ......................................................
117.8
118.7
116.7
119.8
116.3
119.1
120.0
117.7
121.1
117.4
120.0
121.0
118.6
121.9
118.5
120.9
121.9
119.6
123.0
119.3
121.9
122.5
121.0
123.6
120.5
123.0
123.8
121.8
124.8
121.5
123.8
124.4
122.9
125.3
122.6
124.2
124.7
123.6
125.8
123.0
125.1
125.2
124.8
126.3
124.0
0.7
.4
1.0
.4
.8
2.6
2.2
3.1
2.2
2.9
Nonunion.....................................................................
Goods-producing........................................................
Service-producing.......................................................
Manufacturing............................................................
Nonmanufacturing.......................................................
116.8
117.7
116.3
118.1
116.3
117.7
118.6
117.2
119.0
117.2
118.8
119.4
118.4
120.0
118.3
119.5
119.9
119.2
120.6
119.0
120.7
121.5
120.3
122.0
120.2
121.7
122.6
121.1
122.9
121.1
122.7
123.6
122.2
124.0
122.2
123.2
124.1
122.7
124.8
122.5
124.3
125.2
123.8
126.1
123.6
.9
.9
.9
1.0
.9
3.0
3.0
2.9
3.4
2.8
117.8
116.2
117.9
116.2
119.1
117.0
119.3
116.4
120.2
118.1
120.1
117.8
120.7
118.8
121.2
118.1
121.6
120.0
122.8
119.4
122.8
120.8
123.6
120.5
124.0
121.8
124.6
121.3
124.3
122.5
125.0
121.7
125.6
123.7
125.8
122.6
1.0
1.0
.6
.7
3.3
3.1
2.4
2.7
117.1
117.0
118.1
117.8
119.1
118.7
119.8
119.7
120.9
121.3
121.9
122.5
122.9
123.2
123.4
123.5
124.5
124.8
.9
1.1
3.0
2.9
Union ..........................................................................
Goods-producing........................................................
Service-producing.......................................................
Manufacturing ............................................................
Nonmanufacturing ......................................................
113.1
112.2
114.2
113.2
113.0
113.9
113.0
115.1
113.9
113.9
114.8
113.8
116.0
114.6
114.9
115.7
114.8
116.8
115.9
115.5
116.5
115.4
118.0
116.6
116.4
117.6
116.7
118.7
117.8
117.3
118.6
117.5
120.1
118.5
118.6
119.1
117.9
120.6
119.2
119.0
119.8
118.4
121.6
119.8
119.8
.6
.4
.8
.5
.7
2.8
2.6
3.1
2.7
2.9
Nonunion.....................................................................
Goods-producing........................................................
Service-producing.......................................................
Manufacturing ............................................................
Nonmanufacturing.......................................................
114.1
114.4
113.8
115.4
113.5
114.8
115.2
114.6
116.1
114.3
115.9
116.0
115.9
117.0
115.5
116.6
116.7
116.6
117.9
116.1
117.4
117.6
117.2
118.6
116.9
118.3
118.6
118.1
119.5
117.8
119.2
119.5
119.0
120.5
118.7
119.8
120.3
119.5
121.5
119.1
120.8
121.3
120.5
122.7
120.0
.8
.8
.8
1.0
.8
2.9
3.1
2.8
3.5
2.7
114.6
113.6
113.5
113.6
115.7
114.3
114.6
113.7
116.8
115.3
115.2
115.3
117.3
116.0
116.5
115.7
117.8
116.6
117.5
116.6
118.8
117.4
118.3
117.9
120.0
118.5
119.5
118.1
120.2
119.1
120.1
119.0
121.3
120.0
120.9
119.9
.9
.8
.7
.8
3.0
2.9
2.9
2.8
113.9
113.5
114.7
114.4
115.8
115.0
116.5
115.8
117.2
117.0
118.1
118.1
119.1
118.6
119.7
119.0
120.6
120.5
.8
1.3
2.9
3.0
Workers, by region 1
Northeast.....................................................................
South ..........................................................................
Midwest (formerly North Central).....................................
West............................................................................
Workers, by area size ’
Metropolitan areas........................................................
Other areas..................................................................
WAGES AND SALARIES
Workers, by bargaining status *
Workers, by region '
Northeast.....................................................................
South ..........................................................................
Midwest (formerly North Central).....................................
West............................................................................
Workers, by area size’
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
108
M onthly Labor Review
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Federal Reserve Bank of St. Louis
August 1995
M onthly Lab or R eview Technical Note, "Estimation procedures for the
Employment Cost Index,” May 1982.
25.
Percent of full-time employees participating In employer-provided benefit plans, 1980-91
Small
private
establish
ments2
Medium and large private establishments'
Item
1983
1984
1985
1986
1988
1989
9
25
76
25
99
10.0
24
3.8
99
67
11
25
74
25
99
9.8
25
3.7
100
67
9
26
73
26
99
9.8
23
3.6
99
67
10
27
72
26
88
3.2
98
10.1
26
3.7
99
67
10
27
72
26
88
3.2
99
10.0
25
3.7
100
70
11
29
72
26
85
3.2
96
9.4
24
3.3
9e
69
10
26
71
26
84
3.3
97
9.2
22
3.1
97
68
8
30
67
26
80
3.3
92
10.2
21
3.3
96
67
8
37
48
27
47
2.9
84
9.5
11
2.8
88
47
4 17
34
4 58
29
56
3.7
81
10.9
38
2.7
72
97
11
36
56
29
63
3.7
74
13.6
39
2.9
67
95
-
-
-
-
-
_
33
16
37
18
37
26
17
8
57
30
51
33
97
97
97
96
97
96
95
90
92
83
69
93
93
58
98
-
60
99
-
62
99
50
37
37
58
99
53
43
46
62
99
61
52
56
67
99
68
61
66
70
99
70
66
76
79
98
80
74
75
80
97
97
96
81
80
98
97
96
79
83
98
97
94
76
78
98
87
86
82
79
99
99
98
26
46
-
27
49
-
44
36
43
47
51
27
33
36
- $10.13 $11.93 $12.05 $12.80 $19.29 $25.31 $26.60
54
58
56
63
64
66
69
51
- $32.51 $35.93 $38.33 $41.40 $60.07 $72.10 $96.97
42
$25.13
67
$109.34
96
96
96
96
96
96
96
92
94
94
64
85
88
69
-
72
64
72
64
72
66
74
64
73
13
62
72
10
59
76
8
49
71
7
42
71
6
44
78
1
19
67
1
55
67
1
45
40
1980 1981 1982
1991
1990
State and local
governments3
1987
1990
Tlme-off plans
Participants with:
Paid lunch time .........................................
10 10
Average minutes per day.......................... 75 75
Paid rest time...........................................
Average minutes per day.........................
Paid funeral leave..................................... Average days per occurrence................... 99 99
Paid holidays ............................................
Average days per year............................. 10.1 10.2
20 23
Paid personal leave...................................
Average days per year............................. Paid vacations.......................................... 100 99
62 65
Paid sick leave.........................................
Unpaid maternity leave ..............................
Unpaid paternity leave ...............................
-
Insurance plans
Participants in medical care plans..................
Participants with coverage for:
Home health care...................................
Extended care facilities............................
Mental health care..................................
Alcohol abuse treatment..........................
Drug abuse treatment ..............................
Participants with employee contribution
required for:
Self coverage .........................................
Average monthly contribution .................
Family coverage......................................
Average monthly contribution5................
Participants in life insurance plans..................
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.....................................................
35
38
$15.74 $25.53
71
65
$71.89 $117.59
41
43
45
47
48
48
42
45
40
19
31
27
54
50
51
49
51
52
49
46
43
45
26
14
21
Retirement plans
Participants in defined benefit pension plans’ ....
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 .........................................
84
84
84
82
82
80
76
63
63
59
20
93
90
55
98
53
45
-
56
98
50
43
-
58
97
52
45
-
64
97
51
54
55
-
63
97
47
54
56
-
67
97
41
57
61
7 53
64
98
35
57
62
760
59
98
26
55
62
45
62
97
22
64
63
48
55
98
7
56
54
48
54
95
7
58
49
31
92
90
33
100
18
9
89
88
16
100
8
9
-
-
-
-
26
33
36
41
44
17
28
45
Other benefits
Employees eligible for:
Flexible benefits plans ...............................
Reimbursement accounts...........................
-
“
-
-
-
2
5
5
12
9
23
10
36
1
8
5
5
5
31
"
' From 1979 to 1986, data were collected in private sector establishments
with a minimum employment varying from 50 to 250 employees, depending
upon industry. In addition, coverage in service industries was limited. Begin
ning in 1988, data were collected in all private sector establishments
employing 100 workers or more in all industries.
2 Includes private sector establishments with fewer than 100 workers.
3 In 1987, coverage excluded local governments employing fewer than 50
workers. In 1990, coverage included all State and local governments.
4 Data exclude college teachers.
5 Data for 1983 refer to the average monthly employee contribution for
dependent coverage, excluding the employee. Beginning in 1984, data refer
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
to the average monthly employee contribution for family coverage, which
includes the employee.
• Prior to 1985, data on participation in defined benefit pension plans
included a small percentage of workers participating in money purchase
pension plans. Beginning in 1985, these workers were classified as
participating in defined contribution plans.
7 Includes employees who participated in Payroll-based Employee Stock
Ownership Plans. Beginning in 1987, these plans were no longer available.
NOTE: Dash indicates data were not collected in this year.
M onthly Labor Review
August 1995
109
Current Labor Statistics:
C o m pe nsatio n & Industrial Relations
26. Specified compensation and wage rate changes from contract settlements, and wage rate changes under all
agreements, private industry collective bargaining agreements covering 1,000 workers or more (in percent)
Annual average
Quarterly average
Measure
1993
1992
1994
1995
1993
II
III
IV
I
II
III
IV
lp
Rate changes under settlements:
Specified total compensation changes,
settlements covering 5,000 workers or more:
First year of contract....................................
Annual average over life of contract............
3.0
3.1
3.0
2.4
3.2
2.6
1.0
1.4
3.8
2.5
3.0
2.6
3.4
2.9
0.0
1.4
1.5
2.1
1.4
1.6
Specified wage changes, settlements covering
1,000 workers or more:
First year of contract................................
Annual average over life of contract..............
2.7
3.0
2.3
2.1
2.5
2.5
1.1
1.7
2.8
2.0
3.0
2.4
2.0
2.4
1.0
1.9
2.2
2.5
1.9
1.9
3.1
3.0
.9
.8
.7
.4
.8
.9
.6
.3
.8
1.9
.4
.9
1.9
.2
.2
.7
.1
.1
.6
(2>
.5
.2
(2)
.1
.3
i2)
.2
.6
.1
.1
.7
.1
.2
.3
.1
.0
.2
.0
Wage rate changes under all agreements:
Average wage change 1..................................
Source:
Current settlements...................................
Prior settlements......................................
COLA provisions.....................................
1 Because of rounding, total may not equal sum of parts.
2 More than zero but less than 0.05 percent.
M onthly Labor Review
Digitized for110
FRASER
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Federal Reserve Bank of St. Louis
August 1995
» = preliminary.
27. Specified compensation and wage rate changes from contract settlements, and wage rate changes under all
agreements, private industry collective bargaining agreements covering 1,000 workers or more during 4-quarter
periods (in percent)
Average for four quarters endingMeasure
II
1995
1994
1993
IV
III
I»
IV
III
II
I
Rata changes under settlements:
Specified total compensation changes, settlements covering
5,000 workers or more, all industries:
First year of contract.................................................................
Annual average over life of contract ...........................................
2.9
2.9
2.1
2.4
3.0
2.4
3.0
2.3
3.1
2.4
3.1
2.5
2.3
2.4
2.1
2.3
Specified wage changes, settlements covering 1,000 workers or
more:
All industries:
First year of contract..............................................................
Contracts with COLA clauses ................................................
Contracts without COLA clauses............................................
Contracts with either lump sums, COLA, or both......................
Contracts with neither lump sums nor COLA...........................
Annual average over life of contract.........................................
Contracts with COLA clauses ................................................
Contracts without COLA clauses............................................
Contracts with either lump sums, COLA, or both......................
Contracts with neither lump sums nor COLA...........................
2.5
2.7
2.5
2.6
2.5
2.7
2.5
2.8
2.7
2.8
2.0
2.5
1.8
2.3
1.7
2.3
2.1
2.4
2.1
2.5
2.3
2.8
2.1
2.6
2.0
2.1
1.4
2.5
1.9
2.5
2.4
2.7
2.3
2.6
2.1
2.1
1.0
2.5
1.8
2.5
2.2
3.0
1.9
2.8
1.5
2.1
1.5
2.4
2.0
2.2
2.3
2.9
2.0
2.7
1.6
2.2
1.7
2.3
2.1
2.2
2.0
2.7
1.8
2.5
1.6
2.3
2.5
2.3
2.3
2.3
1.8
2.5
1.6
2.3
1.5
2.3
2.4
2.2
2.2
2.3
Manufacturing:
First year of contract..............................................................
Contracts with COLA clauses ................................................
Contracts without COLA clauses...........................................
Contracts with either lump sums, COLA, or both......................
Contracts with neither lump sums nor COLA...........................
Annual average over life of contract.........................................
Contracts with COLA clauses ................................................
Contracts without COLA clauses............................................
Contracts with either lump sums, COLA, or both......................
Contracts with neither lump sums nor COLA...........................
2.0
2.4
3.0
2.3
3.3
2.6
2.3
2.8
2.2
3.0
2.5
2.6
2.5
2.3
3.1
2.1
1.9
2.5
1.8
2.9
2.7
2.9
2.3
2.7
2.9
1.5
1.3
2.1
1.3
2.5
2.5
2.7
1.9
2.4
2.6
1.3
1.0
1.9
1.0
2.3
2.7
3.0
1.9
2.7
2.6
1.5
1.3
2.0
1.4
2.3
2.6
3.0
1.9
2.7
2.2
1.7
1.5
1.9
1.5
2.0
2.4
3.0
1.8
2.4
2.2
2.3
2.5
2.1
2.3
2.2
2.2
2.6
1.8
2.2
2.2
2.1
2.3
1.9
2.1
2.2
Nonmanufacturing:
First year of contract..............................................................
Contracts with COLA clauses ................................................
Contracts without COLA clauses...........................................
Contracts with either lump sums, COLA, or both......................
Contracts with neither lump sums nor COLA...........................
Annual average over life of contract.........................................
Contracts with COLA clauses ................................................
Contracts without COLA clauses...........................................
Contracts with either lump sums. COLA, or both......................
Contracts with neither lump sums nor COLA...........................
2.5
3.0
2.4
2.7
2.4
2.8
2.7
2.8
2.9
2.7
1.7
2.5
1.6
2.3
1.5
2.4
2.7
2.4
2.5
2.4
2.1
1.8
2.1
2.4
1.8
2.5
2.3
2.6
2.6
2.5
2.3
1.9
2.3
2.0
2.0
2.6
2.5
2.6
2.7
2.5
2.0
2.9
1.9
2.9
1.3
2.4
2.7
2.4
2.7
2.2
2.0
2.5
2.0
2.8
1.4
2.5
2.7
2.5
2.7
2.3
1.8
2.2
1.8
2.6
1.6
2.3
Construction:
First year of contract..............................................................
Annual average over life of contract.........................................
1.8
2.4
2.0
2.4
2.1
2.6
2.4
2.7
1.7
2.5
1.8
2.9
2.6
3.0
2.9
.7
1.8
.4
.6
1.8
.3
.9
1.9
.2
.9
1.8
.2
Wage rate changes under all agreements:
Average wage change' ...............................................................
Source:
Current settlements..................................................................
Prior settlements......................................................................
COLA provisions......................................................................
2.3
1.6
2.2
1.5
2.4
1.4
2.3
2.6
2.3
2 .4
2 .4
2.3
2.3
2 .6
1.8
2.5
1.5
2.4
2.7
2.9
2.7
2.6
.9
1.7
.2
.8
1.9
.2
.6
1.9
.2
.5
1.9
.3
2 .6
1 Because of rounding, total may not equal sum of parts.
p = preliminary.
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Federal Reserve Bank of St. Louis
M onthly Labor Review
August 1995
111
Current Labor Statistics:
Compensation & Industrial Relations
28. Specified changes in the cost of compensation and components annualized over the life of the contract in
private industry collective bargaining settlements covering 5,000 workers or more, by quarter, and during 4-quarter
periods (in percent)
1993
Measure
II
III
1994
IV
I
II
1995
III
IV
I
0.8
.9
.9
.5
1.2
1.5
1.5
.6
1.1
1.2
1.1
.9
Quarterly average
All industries:
Compensation.........................................
Cash payments.....................................
Wages..................................................
Benefits......................................
1.8
1.7
1.7
1.8
0.9
.8
.7
1.1
1.8
1.4
1.4
2.4
2.0
1.9
1.7
2.1
1.9
1.4
1.4
2.7
Average for four quarters
All industries:
Compensation.................................
Cash payments................................
Wages.............................................
Benefits.................................................
With contingent pay provisions:
Compensation............................................
Cash payments.....................................................
Wages...........................................................................
Benefits....................................................
Without contingent pay provisions:
Compensation.........................................................................
Cash payments......................................................................
Wages.....................................................
Benefits.................................................
1.9
1.7
1.8
2.3
1.4
1.2
1.3
1.7
1.6
1.3
1.3
2.1
1.6
1.3
1.3
2.0
1.6
1.3
1.3
2.2
1.7
1.4
1.4
2.2
1.6
1.4
1.3
1.8
1.4
1.3
1,3
1.6
2.0
1.7
1.9
2.5
1.4
1.2
1.4
1.8
1.5
1.2
1.4
2.0
1.4
1.2
1.3
1.8
1.7
1.3
1.4
2.3
1.9
1.4
1.6
2.5
2.2
1.8
1.7
3.0
2.1
1.7
1.6
2.8
1.9
1.7
1.7
2.3
1.4
1.3
1.2
1.6
1.7
1.4
1.3
2.1
1.8
1.6
1.4
2.2
1.6
1.3
1.1
2.1
1.5
1.3
1.1
1.8
1.3
1.3
1.2
1.3
1.1
1.1
1.1
1.1
Manufacturing:
Compensation.....................................................................
Cash payments.......................................................................
Wages.................................................................................
Benefits.................................................................
1.8
1.3
1.7
2.7
1.1
1.0
1.2
1.4
1.2
.8
1.1
1.6
1.1
.7
.9
1.5
1.3
.9
1.1
1.9
1.5
1.0
1.2
2.1
1.9
1.7
1.6
2.3
1.7
1.6
1.4
2.0
Nonmanufacturing:
Compensation.........................................................................
Cash payments.......................................................................
Wages...............................................................................
Benefits...............................................................
2.0
1.8
1.8
2.2
1.5
1.3
1.3
1.8
1.9
1.6
1.5
2.4
2.0
1.8
1.6
2.3
1.8
1.5
1.4
2.4
1.8
1.6
1.5
2.2
1.4
1.3
1.3
1.6
1.3
1.2
1.2
1.5
Goods-producing:
Compensation.........................................................................
Cash payments.......................................................................
Wages.................................................................................
Benefits.................................................................................
1.9
1.6
1.8
2.7
1.6
1.4
1.5
2.1
1.4
1.1
1.2
1.9
1.4
1.2
1.2
1.8
1.4
1.1
1.1
1.8
1.4
1.2
1.2
1.8
1.6
1.5
1.4
1.6
1.4
1.3
1.2
1.5
Service-producing:
Compensation.........................................................................
Cash payments.......................................................................
Wages.................................................................................
Benefits..................................................................................
2.0
1.8
1.8
2.2
1.2
1.1
1.0
1.3
1.8
1.5
1.5
2.3
1.8
1.6
1.5
2.2
2.0
1.6
1.5
2.7
2.0
1.6
1.6
2.6
1.5
1.3
1.3
1.9
1.5
1.3
1.3
1.8
112
M onthly Labor Review
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Federal Reserve Bank of St. Louis
*
August 1995
29. Specified compensation and wage rate changes from contract settlements, and wage rate changes under all agreements,
State and local government collective bargaining agreements covering 1,000 workers or more (in percent)
Annual average
Measure
1992
1993
1994
Changes under settlements:
Total compensation 1changes, 2 settlements covering 5,000 workers or more:
First year of contract ................................................................................................................................
Annual average over life of contract...........................................................................................................
0.6
1.9
0.9
1.8
2.8
3.1
Wage changes, settlements covering 1,000 workers or more:
First year of contract ................................................................................................................................
Annual average over life of contract...........................................................................................................
1.1
2.1
1.1
2.1
2.7
3.0
1.9
2.8
3.3
.8
1.1
(4)
1.6
1.1
(4)
1.4
1.9
(4)
Wage changes under all agreements:
Average wage change 3..............................................................................................................................
Source:
Current settlements................................................................................................................................
Prior settlements....................................................................................................................................
COLA provisions....................................................................................................................................
’ Compensation includes wages, salaries, and employers’ cost of employee
benefits when contract is negotiated.
2 Changes are the net result of increases, decreases, and zero change in
compensation or wages.
3 Because of rounding, total may not equal sum of parts.
4 Less than 0.05 percent.
30. Work stoppages involving 1,000 workers or more
1995
1994
Annual totals
Measure
1993
Number of stoppages:
Beginning in period..................
In effect during period..............
1994
June
May
July
Sept.
Aug.
Nov.
Oct.
Apr."
Mar»
Feb.»
Jan.p
Dec.
35
36
45
45
4
6
9
11
4
9
5
11
7
14
4
9
1
6
0
4
1
4
1
4
4
7
2
5
Workers involved:
Beginning in period (in
thousands)............................
In effect during period (in
thousands)............................
18.2
322.2
13.5
38.7
14.3
58.6
32.0
8.0
2.6
.0
37:7
3.0
17.6
32.0
18.4
322.2
18.0
43.2
33.1
88.2
59.4
32.7
26.8
17.2
52.9
18.2
32.8
56.9
Days idle:
Number (in thousands).............
Percent of estimated working
time' ....................................
3,981.0
5,020.5
133.5
367.0
436.1
678.5
638.5
505.9
420.8
342.2
368.5
306.8
367.8
529.7
.02
.01
.01
.01
.01
.01
.02
.02
.01
.02
' 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
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
.02
.02
.02
.02
worked is found in "Total economy’ measure of strike idleness." M onthly Labor R e
view, October 1968, pp. 54-56.
p = preliminary.
M onthly Labor Review
August 1995
113
Current Labor Statistics:
Price D a ta
31. 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
Series
1994
1995
*
1993
1994
May
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
CONSUMER PRICE INDEX FOR ALL URBAN CONSUMERS:
All items.....................
All items (1967 = 100) ........
144.5 148.2 147.5 148.0 148.4 149.0 149.4 149.5 149.7 149.7 150.3 150.9 151.4 151.9 152.2
432.7 444.0 441.9 443.3 444.4 446.4 447.5 448.0 448.6 448.4 450.3 452.0 453.5 455.0 455.8
Food and beverages...........
Food............................
Food at home..............
Cereals and bakery products..........................................
Meats, poultry, fish, and eggs.........................................
Dairy products........................
Fruits and vegetables.....................................................
Other foods at home.....................................................
Sugar and sweets.......................................................
Fats and oils........................
Nonalcoholic beverages........
Other prepared foods.................
Food away from home ................
Alcoholic beverages...................
141.6
140.9
140.1
156.6
135.5
129.4
159.0
130.5
133.4
130.0
114.6
143.7
143.2
149.6
144.9
144.3
144.1
163.0
137.2
131.7
165.0
135.6
135.2
133.5
123.2
147.5
145.7
151.5
144.1
143.5
143.0
162.3
137.1
132.0
163.2
132.8
135.5
133.4
115.6
147.0
145.3
151.5
144.2
143.5
142.9
163.4
137.2
132.2
161.6
132.9
134.9
133.5
115.8
147.2
145.5
151.7
144.8
144.2
144.0
163.9
136.7
131.8
164.4
135.7
135.2
135.1
122.8
147.6
145.6
151.6
145.3
144.8
144.7
164.7
137.1
131.8
162.8
138.9
135.1
134.1
131.3
148.4
145.9
151.3
145.6
145.0
145.0
164.8
137.3
131.3
163.2
139.4
135.4
134.2
132.1
148.8
146.2
151.4
145.6
145.0
144.8
164.6
136.8
131.5
162.9
139.5
135.6
135.0
132.7
148.5
146.4
151.6
145.9
145.3
145.1
163.7
136.9
131.7
165.7
139.0
134.5
134.3
132.4
148.1
146.8
151.9
147.2
146.8
147.3
164.2
136.4
131.6
180.3
138.8
134.5
134.2
131.7
148.1
147.1
151.8
147.9
147.5
148.2
164.6
137.3
132.7
180.4
140.3
135.5
136.4
133.3
149.4
147.4
152.0
147.8
147.4
147.9
165.8
137.6
132.1
177.1
140.6
135.8
136.8
133.7
149.7
147.6
152.4
147.9
147.4
147.6
165.3
138.4
132.2
174.0
140.7
136.4
136.8
132.9
150.5
148.1
153.1
148.9
148.4
149.2
166.9
137.7
132.1
183.1
140.9
136.7
137.2
132.9
150.6
148.3
153.6
148.7
148.3
148.7
166.6
137.3
132.8
181.0
140.8
137.3
137.1
131.7
151.3
148.6
153.9
Housing ...............................
Shelter..........................
Renters' costs (12/82= 100)............................................
Rent, residential...........................
Other renters' costs .......................
Homeowners' costs (12/82 = 100)....................................
Owners' equivalent rent (12/82=100).............................
Household insurance (12/82=100).................................
Maintenance and repairs...................
Maintenance and repair services ....................................
Maintenance and repair commodities...............................
Fuel and other utilities....................
Fuels ......................................
Fuel oil, coal, and bottled gas................
Gas (piped) and electricity ..........................
Other utilities and public services.................
Household furnishings and operations..................................
Housefurnishings ....................
Housekeeping supplies....................................................
Housekeeping services.....................................................
141.2
155.7
165.0
150.3
190.3
160.2
160.5
146.9
130.6
135.0
124.6
121.3
111.2
90.3
118.5
147.0
119.3
109.5
130.7
135.8
144.8
160.5
169.4
154.0
196.3
165.5
165.8
152.3
130.8
134.5
125.8
122.8
111.7
88.8
119.2
150.2
121.0
111.0
132.3
138.5
144.1
159.6
168.5
153.3
194.9
164.5
164.8
150.8
131.0
135.0
125.7
122.2
110.6
88.7
118.0
150.4
121.1
111.4
131.9
138.1
144.9
160.1
169.6
153.4
198.9
164.8
165.1
151.9
131.5
135.4
126.2
124.2
113.9
87.7
122.1
150.4
121.4
111.6
132.4
138.4
145.4
160.8
171.0
153.9
203.2
165.3
165.5
153.2
131.3
135.4
125.9
124.3
114.1
87.1
122.3
150.4
121.5
111.8
132.2
138.6
145.9
161.7
172.1
154.5
205.9
166.1
166.4
154.0
131.2
135.4
125.6
124.3
114.0
86.8
122.2
150.6
121.4
111.5
132.2
138.9
145.8
161.6
169.4
155.0
193.5
167.1
167.3
154.3
131.6
135.8
126.0
124.2
113.8
86.8
122.1
150.3
121.4
111.2
132.6
139.3
145.7
162.0
169.8
155.2
194.0
167.5
167.8
154.5
130.8
135.9
123.8
122.4
110.8
87.0
118.5
150.4
121.4
110.9
133.7
139.4
145.5
162.1
168.9
155.6
189.2
167.9
168.2
155.0
131.2
136.4
124.3
121.8
109.9
87.7
117.3
150.5
121.1
110.8
132.6
139.1
145.4
161.8
168.2
155.7
186.2
167.8
168.1
155.4
132.7
137.0
126.8
122.0
110.1
88.4
117.4
150.6
120.8
110.3
132.9
139.1
146.4
162.9
170.7
156.1
195.0
168.4
168.7
155.9
133.1
137.3
127.5
122.9
110.7
89.4
118.0
152.1
121.8
110.5
133.8
142.4
147.0
163.8
172.9
156.4
202.9
168.9
169.1
156.1
133.8
137.9
128.2
122.6
110.4
89.6
117.6
151.8
122.4
111.1
134.6
142.8
147.4
164.5
174.6
156.7
208.7
169.2
169.5
157.1
134.2
138.8
128.2
122.3
109.8
89.0
117.1
151.9
122.6
111.2
135.7
142.9
147.4
164.7
174.1
157.0
206.0
169.6
169.9
157.2
134.2
139.0
127.6
122.1
109.3
88.4
116.6
152.2
122.6
111.2
135.9
142.9
147.6
164.8
173.7
157.2
203.4
170.0
170.3
157.4
134.6
139.4
128.1
122.5
109.8
88.3
117.2
152.3
122.7
111.0
136.4
143.3
Apparel and upkeep ........................
Apparel commodities ...................
Men’s and boys' apparel..................................................
Women's and girls' apparel ..............................................
Infants' and toddlers' apparel............................................
Footwear............................
Other apparel commodities.....................
Apparel services.......................
133.7 133.4
131.0 130.4
127.5 126.4
132.6 130.9
127.1 128.1
125.9 126.0
145.6 149.5
151.7 155.4
135.6
132.8
127.4
135.1
125.2
128.5
149.9
155.0
133.8
130.8
125.9
131.6
128.4
127.3
149.7
155.5
130.9 131.1 134.2
127.6 127.8 131.2
124.9 125.7 128.4
125.7 125.5 131.1
129.2 128.6 129.5
125.0 124.5 125.1
150.6 152.4 152.3
155.7 155.9 156.3
135.2
132.3
128.9
133.4
128.6
125.5
151.4
156.4
134.2
131.1
129.2
130.5
131.2
125.7
150.8
156.3
130.5
127.2
125.3
125.7
131.3
123.6
146.5
156.4
129.4 131.1
126.0 127.7
124.0 125.6
123.0 125.9
129.0 126.8
124.0 124.8
150.1 150.4
157.0 157.3
134.4
131.3
127.2
131.5
127.1
125.9
155.0
157.6
134.8
131.7
127.0
132.2
127.1
127.2
154.4
157.7
133.4
130.2
127.9
129.6
123.6
126.6
150.3
157.7
Transportation ..................................
Private transportation........................
New vehicles ...............................
New cars...............................
Used cars.....................................
Motor fuel................................
Gasoline...............................
Maintenance and repair............
Other private transportation...........................
Other private transportation commodities...................
Other private transportation services..............
Public transportation........................
130.4 134.3 132.8 133.8 134.6 135.9
127.5 131.4 130.0 131.0 131.8 133.0
132.7 137.6 137.2 137.4 137.4 137.3
131.5 136.0 135.7 135.8 135.8 135.6
133.9 141.7 137.9 140.9 142.6 144.0
98.0 98.5 96.0 98.2 100.5 104.1
97.7 98.2 95.6 97.9 100.4 104.1
145.9 150.2 149.7 149.8 150.0 150.7
156.8 162.1 160.8 161.3 161.5 162.0
103.4 103.5 103.4 103.4 103.3 103.3
169.1 175.8 174.0 174.8 175.1 175.7
167.0 172.0 169.9 169.9 171.4 173.2
135.9
133.1
137.5
135.7
145.4
103.7
103.6
151.2
162.1
103.2
175.8
171.7
136.1
133.6
138.4
136.6
147.7
101.8
101.7
151.7
164.1
103.1
178.4
168.4
137.1
134.8
139.4
137.7
150.1
102.7
102.6
151.8
166.2
104.0
180.7
167.2
137.1 137.3
134.9 134.9
140.1 140.6
138.5 139.0
151.5 152.4
100.4 98.7
100.2 984
151.9 152.0
167.6 168.8
104.3 104.2
182.4 184.0
165.6 168.4
137.5
135.0
140.7
139.1
153.3
98.0
97.7
152.5
169.4
104.6
184.6
169.9
138.0 139.1
135.2 136.2
140.7 141.1
139.0 139.3
154.8 156.7
97.5 99.5
97.2 99.3
152.7 153.2
170.2 170.9
104.6 104.5
185.6 186.5
174.5 176.7
140.3
137.5
141.1
139.3
157.7
104.2
104.2
153.8
170.5
104.7
185.9
176.7
Medical care..................................
Medical care commodities ........................
Medical care services.............................
Professional services......................
Hospital and related services...........................
201.4
195.0
202.9
184.7
231.9
211.0
200.7
213.4
192.5
245.6
209.7
200.1
212.0
191.7
243.5
210.4
200.5
212.6
192.3
244.1
211.5
201.3
213.8
193.0
246.1
212.2
201.7
214.7
193.5
247.3
212.8
201.7
215.4
194.0
248.1
214.0
202.2
216.8
195.1
249.8
214.7
202.7
217.5
195.5
250.6
215.3
202.9
218.2
196.0
251.3
216.6
203.1
219.8
197.2
253.2
217.9
203.5
221.3
198.5
254.7
218.4
203.7
221.8
199.1
254.7
218.9
203.6
222.4
199.5
255.3
219.3
203.4
223.0
200.2
255.6
Entertainment ....................................
Entertainment commodities .........................
Entertainment services...............................
145.8
133.4
160.8
150.1
136.1
166.8
149.9
136.2
166.2
149.8
136.1
166.3
150.2
136.5
166.7
150.2
136.5
166.6
150.7
137.0
167.1
151.0
136.9
167.7
151.6
137.3
168.6
151.2
136.8
168.3
152.1
137.5
169.4
152.5
137.4
170.2
152.6
137.3
170.7
153.3
138.1
171.3
153.6
138.1
171.8
Other goods and services ............................
Tobacco products ...................................
Personal care......................................
Toilet goods and personal care appliances........................
Personal care services ..............................
Personal and educational expenses....................................
School books and supplies.............................................
Personal and educational services....................................
192.9
228.4
141.5
139.0
144.0
210.7
197.6
211.9
198.5
220.0
144.6
141.5
147.9
223 2
205.5
224.8
197.1
220.6
144.4
141.7
147.2
220.4
204.1
221.9
197.6
220.6
145.2
141.8
148.8
220.9
204.6
222.4
198.0
221.3
145.0
141.9
148.3
221.6
205.1
223.0
199.4
221.7
145.0
141.9
148.3
223.9
205.8
225.5
201.4
220.8
145.1
141.8
148.7
228.0
208.4
229.7
201.9
221.3
145.3
142.0
148.7
228.8
207.7
230.6
202.3
221.4
145.7
142.3
149.2
229.2
207.7
231.1
202.4
222.0
145.8
142.6
149.2
229.2
207.4
231.1
203.0
222.2
145.7
142.2
149.4
230.2
211.9
231.8
204.1
222.7
146.2
142.6
150.1
232.0
212.5
233.6
204.0
222.5
146.0
142.2
150.2
232.0
212.6
233.6
204.3
223.0
146.3
142.2
150.7
232.1
212.7
233.8
204.9
225.3
146.6
142.9
150.6
232.3
212.2
234.0
See footnotes at end of table.
M onthly Labor Review
Digitized for114
FRASER
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
August 1995
31. Continued— Consumer Price Indexes for All Urban Consumers and for Urban Wage Earners and Clerical Workers: U.S. city
average, by expenditure category and commodity or service group
(1982-84 = 100, unless otherwise indicated)
Series
1993
All items...............................................................................
Commodities................................................... ....................
Food and beverages..........................................................
Commodities less food and beverages.................................
Nondurables less food and beverages ...............................
Apparel commodities.....................................................
Nondurables less food, beverages, and apparel ...............
Durables.........................................................................
1994
144.5 148.2
131.5 133.8
141.6 144.9
125.3 126.9
128.1 128.4
131.0 130.4
129.6 130.3
121.3 124.8
1995
1994
Annual
average
May
June
July
Aug.
147.5
133.4
144.1
126.8
128.5
132.8
129.3
124.4
148.0
133.5
144.2
126.9
128.4
130.8
130.2
124.9
148.4
133.7
144.8
126.8
128.1
127.6
131.3
125.1
149.0
134.3
145.3
127.5
129.2
127.8
132.8
125.1
Services..............................................................................
Rent of shelter (12/82-100)..............................................
Household services less rent of’ shelter (12/82=100)...........
Transportation services......................................................
Medical care services.........................................................
Other services ..................................................................
157.9 163.1 162.0 162.8
162.0 167.0 166.0 166.6
134.2 136.3 135.7 137.7
162.9 168.6 167.1 167.5
202.9 213.4 212.0 212.6
177.0 185.4 183.9 184.3
Special indexes:
All items less food .............................................................
All items less shelter.........................................................
All items less homeowners' costs (12/82-100)....................
All items less medical care......................... ........................
Commodities less food.......................................................
Nondurabies less food .......................................................
Nondurables less food and apparel .....................................
Nondurables......................................................................
Services less rent of’ shelter (12/82-100)...........................
Services less medical care.................................................
Energy..............................................................................
All items less energy .........................................................
All items less food and energy ............................................
Commodities less food and energy......................................
Energy commodities ..........................................................
Services less energy..........................................................
145.1
141.4
146.0
141.2
126.3
129.3
130.7
135.1
164.8
153.6
104.2
150.0
152.2
135.2
97.3
161.9
149.0
144.8
149.5
144.7
127.9
129.7
131.6
136.8
170.7
158.4
104.6
154.1
156.5
137.1
97.6
167.6
148.3
144.2
148.9
144.0
127.8
129.8
130.6
136.5
169.5
157.4
102.9
153.5
156.0
137.5
95.4
166.6
Purchasing power of the consumer dollar:
1982-84-$1.00.................................................................
1967 —$1.00......................................................................
69.2
23.1
67.5
22.5
67.8
22.6
Oct.
149.4 149.5
134.8 134.9
145.6 145.6
128.1 128.3
130.3 130.2
131.2 132.3
132.8 132.2
125.1 125.7
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
149.7
135.2
145.9
128.6
130.1
131.1
132.5
126.5
149.7
135.1
147.2
127.6
128.1
127.2
131.5
126.9
150.3
135.1
147.9
127.4
127.5
126.0
131.2
127.2
150.9
135.4
147.8
127.9
128.1
127.7
131.3
127.6
151.4
135.9
147.9
128.6
129.2
131.3
131.1
127.7
151.9
136.6
148.9
129.2
129.9
131.7
132.0
128.1
152.2
136.9
148.7
129.7
130.8
130.2
134.2
128.1
163.4 164.2 164.4 164.6 164.7 164.7 165.9 166.7 167.3 167.5 167.7
167.3 168.2 168.2 168.6 168.6 168.3 169.4 170.4 171.2 171.3 171.5
137.9 138.0 137.9 136.3 135.8 135.9 137.2 137.0 136.9 136.7 137.1
168.1 168.9 168.8 169.5 170.5 171.1 172.6 173.4 175.0 176.1 175.9
213.8 214.7 215.4 216.8 217.5 218.2 219.8 221.3 221.8 222.4 223.0
184.7 185.8 187.8 188.5 189.0 188.9 189.7 190.9 191.1 191.4 191.7
148.8 149.1
144.6 144.9
149.4 149.8
144.5 144.8
127.9 127.8
129.7 129.4
131.4 132.4
136.5 136.6
170.5 171.0
158.2 158.7
105.7 106.8
153.7 154.0
156.2 156.4
137.3 136.8
97.2 99.2
167.1 167.7
67.6
22.6
Sept.
67.4
22.5
149.8 150.2 150.4
145.5 146.0 146.1
150.4 150.6 150.7
145.5 145.8 145.9
128.4 129.0 129.3
130.4 131.4 131.4
133.7 133.7 133.2
137.4 138.1 138.1
171.7 172.2 172.2
159.4 159.6 159.7
108.5 108.2 105.8
154.6 155.0 155.5
157.0 157.5 158.0
136.8 137.7 138.3
102.4 102.0 100.4
168.5 168.8 169.3
67.1
22.4
66.9
22.3
66.9
22.3
150.6
146.3
150.9
146.1
129.5
131.2
133.5
138.2
172.4
159.8
105.7
155.7
158.2
138.4
101.2
169.6
150.2
146.3
150.8
146.0
128.5
129.5
132.6
137.8
172.7
159.7
104.7
155.7
157.9
137.6
99.2
169.6
150.8
146.8
151.5
146.6
128.3
128.9
132.4
137.8
174.0
160.9
104.2
156.5
158.7
137.7
97.9
170.8
151.5
147.2
152.1
147.1
128.8
129.5
132.5
138.1
174.7
161.6
103.7
157.2
159.6
138.4
97.2
171.7
66.8
22.3
66.8
22.3
66.5
22.2
66.3
22.1
152.1 152.5
147.7 148.3
152.7 153.2
147.6 148.1
129.5 130.1
130.5 131.3
132.4 133.3
138.7 139.6
175.1 175.5
162.2 162.4
103.2 103.9
157.8 158.3
160.4 160.7
139.4 139.7
96.7 98.4
172.4 172.7
152.9
148.6
153.4
148.4
130.6
132.1
135.2
139.9
175.8
162.6
106.3
158.3
160.8
139.6
102.6
172.9
65.8
22.0
65.7
21.9
66.0
22.0
CONSUMER PRICE INDEX FOR URBAN WAGE EARNERS
AND CLERICAL WORKERS:
All items ...............................................................................
All items (1967-100) .............................................................
142.1
423.1
145.6 144.9 145.4 145.8 146.5 146.9 147.0 147.3 147.2 147.8 148.3 148.7 149.3 149.6
433.8 431.7 433.2 434.3 436.4 437.5 437.8 438.6 438.6 440.2 441.7 443.0 444.6 445.6
Food and beverages ............................................................
Food................................................................................
Food at home .................................................................
Cereals and bakery products.........................................
Meats, poultry, fish, and eggs.........................................
Dairy products..............................................................
Fruits and vegetables....................................................
Other foods at home.....................................................
Sugar and sweets.......................................................
Fats and oils..............................................................
Nonalcoholic beverages...............................................
Other prepared foods..................................................
Food away from home .....................................................
Alcoholic beverages...........................................................
141.2
140.5
139.6
156.3
135.4
129.1
158.2
130.4
133.1
129.9
115.1
143.5
143.1
149.3
144.4
143.9
143.4
162.7
137.0
131.5
164.2
135.3
135.2
133.5
122.9
147.2
145.5
151.0
143.7
143.1
142.4
162.0
137.0
131.7
162.3
132.7
135.4
133.4
116.1
146.7
145.2
150.9
143.8
143.2
142.4
163.1
137.0
132.1
161.1
132.7
134.7
133.4
116.2
146.9
145.4
151.3
144.4
143.8
143.4
163.6
136.4
131.6
163.8
135.4
135.1
135.1
122.4
147.4
145.5
151.1
144.9
144.4
144.1
164.4
136.9
131.6
162.3
138.3
135.1
134.0
130.2
148.1
145.8
150.7
145.1
144.6
144.4
164.6
137.2
131.0
162.6
138.8
135.4
134.2
130.9
148.5
146.1
150.9
145.1
144.6
144.1
164.3
136.6
131.2
162.0
139.0
135.7
135.0
131.5
148.2
146.3
151.1
145.3
144.8
144.3
163.5
136.7
131.4
164.5
138.5
134.5
134.1
131.1
147.8
146.7
151.3
146.6
146.2
146.3
163.9
136.0
131.4
178.8
138.3
134.4
134.1
130.6
148.0
147.0
151.4
147.2
146.9
147.2
164.3
137.1
132.4
178.8
139.7
135.5
136.3
132.2
149.1
147.3
151.6
147.3
146.9
147.1
165.6
137.4
131.8
175.8
140.2
135.8
136.7
132.9
149.5
147.5
152.0
147.3
146.8
146.8
165.1
138.1
131.9
172.7
140.3
136.4
136.7
132.2
150.2
147.9
152.7
148.3
147.9
148.2
166.7
137.3
131.8
182.1
140.4
136.6
137.1
132.1
150.3
148.2
153.2
148.1
147.7
147.8
166.3
136.9
132.5
179.8
140.4
137.3
136.9
131.0
151.0
148.5
153.4
Housing ..............................................................................
Shelter .............................................................................
Renters’ costs (12/84 = 100)............................................
Rent, residential............................................................
Other renters' costs ......................................................
Homeowners' costs (12/84 = 100).....................................
Owners’ equivalent rent (12/84 = 100) .............................
Household insurance (12/84 = 100).................................
Maintenance and repairs..................................................
Maintenance and repair services ....................................
Maintenance and repair commodities...............................
Fuel and other utilities........................................................
Fuels .............................................................................
Fuel oil, coal, and bottled gas ........................................
Gas (piped) and electricity .............................................
Other utilities and public services ......................................
Household furnishings and operations..................................
Housefurnishings .............................................................
Housekeeping supplies.....................................................
Housekeeping services.....................................................
138.5
151.6
144.7
150.0
190.2
146.1
146.3
134.4
130.9
138.6
120.7
121.1
110.7
90.2
118.0
147.7
118.0
108.3
131.1
137.4
142.0
156.2
148.5
153.7
196.6
150.9
151.1
139.7
130.8
138.1
121.1
122.5
111.1
88.7
118.7
150.8
119.7
109.6
132.5
140.6
141.3
155.3
147.7
153.0
194.9
150.0
150.2
138.1
130.9
138.8
120.6
121.9
110.0
88.6
117.4
151.0
119.7
109.9
132.2
140.2
142.1
155.8
148.4
153.1
199.1
150.3
150.5
139.1
131.5
139.1
121.4
124.0
113.5
87.6
121.5
151.1
120.0
110.1
132.7
140.3
142.5
156.4
149.5
153.6
204.2
150.7
150.9
140.5
131.4
139.1
121.1
124.0
113.6
87.0
121.7
150.9
120.1
110.3
132.5
140.6
143.0
157.2
150.3
154.2
206.7
151.5
151.7
141.4
131.3
139.1
120.9
124.0
113.5
86.6
121.6
151.1
120.0
110.1
132.5
140.9
143.0
157.4
148.9
154.7
194.1
152.3
152.6
141.7
131.8
139.4
121.6
123.9
113.3
86.7
121.5
150.9
120.0
109.8
132.9
141.5
142.8
157.7
149.2
154.9
194.4
152.8
153.0
141.9
131.0
139.5
120.0
122.0
110.2
86.9
117.8
150.9
120.1
109.5
133.9
141.7
142.7
157.9
148.8
155.4
189.6
153.1
153.3
142.4
131.4
140.0
120.2
121.5
109.3
876
116.7
150.9
119.8
109.5
133.0
141.4
142.7
157.7
148.5
155.4
187.2
153.1
153.3
142.9
132.4
140.3
121.9
121.6
109.5
88.3
116.8
151.1
119,7
109.1
133.3
141.5
143.5
158.6
149.9
155.7
195.3
153.6
153.8
143.2
132.8
140.5
122.5
122.5
110.1
89.3
117.4
152.4
120.5
109.2
134.1
145.6
144.0
159.3
151.3
156.1
202.9
154.0
154.2
143.4
133.2
140.8
123.0
122.2
109.7
89.5
116.9
152.2
121.2
109.9
134.8
146.0
144.3
159.9
152.3
156.4
208.5
154.3
154.5
144.2
133.7
141.7
123.1
121.9
109.1
88.9
116.3
152.3
121.4
109.9
135.9
146.1
144.4
160.1
152.1
156.7
205.8
154.7
154.9
144.5
133.7
141.9
122.9
121.6
108.4
88.3
115.6
152.7
121.4
109.9
136.2
145.9
144.6
160.3
152.0
156.9
203.8
155.1
155.3
144.6
134.1
142.3
123.2
122.0
109.1
88.2
116.3
152.8
121.5
109.8
136.6
146.2
...
.
See footnotes at end of table.
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
M onthly Labor Review
August 1995
115
Current Labor Statistics:
Price D ata
31. 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
1994
1995
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
129.8 130.2
126.7 127.2
124.6 125.3
124.2 124.5
130.8 129.9
125.8 125.3
148.3 151.5
155.1 155.4
133.1
130.2
127.8
129.4
131.1
126.0
151.3
155.9
133.9
131.1
128.1
131.7
130.3
126.3
149.9
156.0
133.0
130.1
128.4
129.1
133.2
126.1
149.1
155.8
129.3
126.1
124.5
124.0
132.9
124.2
144.1
155.9
128.3
125.0
123.5
121.2
130.3
124.4
149.1
156.5
130.0
126.8
125.2
124.3
127.0
125.3
149.7
156.8
133.2
130.3
126.7
129.8
127.4
126.8
154.6
157.1
133.6 132.1
130.7 129.1
126.5 127.8
130.6 128.1
127.7 123.9
127.9 127.4
153.5 146.9
157.2 157.1
133.9
132.0
138.3
135.6
143.3
100.5
100.4
150.8
157.5
102.6
171.0
167.1
135.3 135.6 136.7
133.5 133.9 135.1
138.4 139.2 140.1
135.4 136.3 137.3
146.1 148.4 150.8
103.7 101.7 102.6
103.7 101.5 102.5
151.9 152.4 152.5
158.0 160.0 162.0
102.4 102.4 103.2
171.8 174.3 176.6
167.6 164.8 163.8
136.7 136.9
135.2 135.2
140.9 141.2
138.1 138.6
152.1 153.0
100.2 98.5
100.0 98.3
152.6 152.7
163.4 164.7
103.5 103.4
178.4 180.0
162.5 164.8
137.1
135.4
141.4
138.7
154.0
97.8
97.5
153.3
165.4
103.8
180.9
166.5
137.6
135.7
141.5
138.7
155.5
97.3
97.0
153.5
166.3
103.8
181.9
170.1
138.7
136.8
141.9
139.0
157.4
99.5
99.3
154.0
166.9
103.7
182.8
172.3
140.1
138.3
141.9
138.9
158.4
104.2
104.3
154.6
166.5
103.9
182.2
172.5
214.0
200.6
217.1
196.5
247.7
214.6
200.8
217.7
196.9
248.5
215.9
200.9
219.3
198.1
250.5
217.3
201.3
220.9
199.4
252.1
217.7
201.5
221.4
200.0
252.2
218.2
201.3
222.0
200.5
252.8
218.7
201.0
222.6
201.2
253.1
149.0
136.2
167.5
149.6
136.6
168.5
149.2
136.1
168.3
150.1
136.8
169.2
150.4
136.8
170.1
150.6
136.7
170.6
151.3
137.5
171.2
151.5
137.5
171.8
198.9
221.1
145.4
142.6
148.6
223.6
209.8
225.0
199.4
221.6
145.5
142.8
148.6
224.4
208.8
225.9
199.8
221.7
145.9
143.1
149.1
224.9
208.8
226.5
200.0
222.2
146.1
143.5
149.2
224.9
208.5
226.5
200.5
222.4
146.0
143.1
149.5
226.0
213.4
227.2
201.5
222.9
146.4
143.4
150.1
227.5
213.4
228.9
201.4
222.6
146.1
142.9
150.2
227.7
213.6
229.0
201.7
223.1
146.5
143.1
150.7
227.8
213.7
229.2
202.5
225.4
146.8
143.7
150.6
228.0
213.2
229.5
146.9
134.6
145.1
128.1
129.9
130.2
132.8
124.4
147.0
134.7
145.1
128.2
129.7
131.1
132.0
125.1
147.3
135.0
145.3
128.6
129.7
130.1
132.4
126.0
147.2
134.8
146.6
127.6
127.7
126.1
131.3
126.5
147.8
134.9
147.2
127.4
127.0
125.0
130.9
126.8
148.3
135.3
147.3
127.9
127.6
126.8
130.8
127.2
148.7
135.7
147.3
128.6
128.5
130.3
130.6
127.5
149.3
136.5
148.3
129.3
129.4
130.7
131.7
128.0
149.6
136.9
148.1
130.0
130.5
129.1
134.2
128.1
1993
1994
May
June
July
Apparel and upkeep.......................
Apparel commodities...........................
Men’s and boys’ apparel........................................
Women's and girls' apparel ..................
Infants’ and toddlers’ apparel.............
Footwear.........................................
Other apparel commodities....................................
Apparel services......................
132.4
129.8
126.8
130.4
128.9
126.5
145.4
151.2
132.2
129.4
125.8
129.2
129.3
126.9
148.7
154.9
134.3
131.6
126.5
132.7
126.2
129.5
151.3
154.5
132.4
129.6
125.3
129.5
129.6
128.2
148.3
155.0
Transportation ............................
Private transportation.................................
New vehicles.................................
New cars.....................................
Used cars.......................
Motor fuel ......................
Gasoline............................................
Maintenance and repair....................................................
Other private transportation..............................................
Other private transportation commodities.........................
Other private transportation services...............................
Public transportation................................................
129.4 133.4 131.8 132.9
127.4 131.4 129.8 131.0
133.3 138.3 138.0 138.2
131.2 135.7 135.4 135.6
134.6 142.4 138.6 141.5
97.9 98.4 96.0 98.2
97.6 98.2 95.6 97.9
146.5 150.9 150.5 150.5
152.9 157.9 156.6 157.3
102.8 102.8 102.8 102.8
165.0 171.5 169.8 170.7
163.0 167.7 166.4 165.9
Medical care...........................................................
Medical care commodities.................................................
Medical care services...........................................
Professional services..................................................
Hospital and related services ...........................................
200.9 210.4 209.1 209.7 210.8 211.5 212.0 213.4
193.2 198.6 198.2 198.7 199.0 199.5 199.3 199.9
202.7 213.0 211.5 212.2 213.4 214.2 214.9 216.4
185.2 193.4 192.5 193.1 193.9 194.4 194.9 196.0
229.2 242.7 240.5 241.3 243.2 244.4 245.2 246.9
Entertainment .............................................................
Entertainment commodities ................................................
Entertainment services.......................................................
144.1
132.9
160.5
148.2
135.5
166.7
148.1
135.7
166.1
148.0
135.6
166.2
148.4
136.0
166.5
148.3
135.9
166.5
148.6
136.0
167.0
Other goods and services ....................................................
Tobacco products .............................................................
Personal care....................................................................
Toilet goods and personal care appliances.........................
Personal care services ....................................................
Personal and educational expenses.....................................
School books and supplies...............................................
Personal and educational services....................................
192.2
228.3
141.6
139.6
143.9
206.9
199.2
207.8
196.4
220.1
144.8
142.2
147.9
219.2
207.1
220.4
195.3
220.6
144.7
142.4
147.3
216.6
205!9
217.7
195.8
220.7
145.3
142.3
149.0
217.2
206.4
218.4
196.3
221.4
145.1
142.5
148.2
217.9
206.9
219.0
197.5
222.1
145.2
142.6
148.2
220.2
207.5
221.5
All items...........................................................
Commodities.................................................
Food and beverages..........................................................
Commodities less food and beverages.................................
Nondurables less food and beverages ...............................
Apparel commodities.....................................................
Nondurables less food, beverages, and apparel ...............
Durables.........................................................................
142.1
131.2
141.2
125.0
127.7
129.8
129.7
120.1
145.6
133.4
144.4
126.6
127.9
129.4
130.1
123.8
144.9
132.9
143.7
126.3
127.9
131.6
129.0
123.1
145.4
133.2
143.8
126.6
127.9
129.6
130.0
123.8
145.8
133.4
144.4
126.7
127.8
126.7
131.2
124.2
146.5
134.1
144.9
127.5
129.1
127.2
133.0
124.3
Services........................................................
Rent of shelter (12/84 = 100)..............................................
Household services less rent of shelter (12/84 = 100)............
Transportation services......................................................
Medical care services.......................................................
Other services ............................................................
M onthly Labor Review
Digitized 116
for FRASER
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
August 1995
135.2
133.3
138.2
135.3
144.7
104.2
104.3
151.4
157.8
102.6
171.5
168.7
155.5 160.6 159.6 160.4 160.9 161.6 161.9 162.1 162.3 162.4
145.8 150.3 149.4 149.9 150.5 151.3 151.4 151.8 151.9 151 7
123.5 125.4 124.8 126.7 126.8 126.9 126.9 125.2 124.7 124.9
160.0 165.7 164.3 164.8 165.2 165.9 166.0 167.2 168.4 169.2
202.7 213.0 211.5 212.2 213.4 214.2 214.9 216.4 217.1 217.7
174.1 182.4 181.0 181.5 181.8 182.9 184.7 185.3 185.9 185.9
Special indexes:
All items less food ............................................................. 142.3 145.9
All items less shelter ......................................................... • 139.7 143.0
All items less homeowners’ costs (12/84 = 100).................... 133.9 137.0
All items less medical care................................................. 139.2 142.6
Commodities less food....................................................... 125.9 127.6
Nondurables less food ....................................................... 128.9 129.2
Nondurables less food and apparel ..................................... 130.7 131.2
Nondurables..................................................................... 134.7 136.4
Services less rent of shelter (12/84 = 100)........................... 147.0 152.1
Services less medical care................................................. 151.4 156.1
Energy.............................................................................. 103.6 104.1
All items less energy ......................................................... 147.5 151.5
All items less food and energy ............................................ 149.3 153.5
Commodities less food and energy...................................... 134.3 136.2
Energy commodities ..........................................................
97.5 97.8
Services less energy.......................................................... 159.7 165.3
Purchasing power of the consumer dollar:
1982-84 -$1 00 .................................................................
1967 = $1.00......................................................................
Aug.
70.4
23.6
68.7
23.1
145.2
142.3
136.4
141.9
127.3
129.2
130.3
136.1
151.0
155.1
102.3
150.9
152.9
136.4
95.6
164.3
145.8
142.8
136.9
142.4
127.6
129.2
131.2
136.1
152.1
155.9
105.1
151.1
153.2
136.3
97.5
164.7
146.1
143.1
137.3
142.7
127.7
129.1
132.2
136.4
152.5
156.4
106.3
151.4
153.4
135.9
99.6
165.3
146.8
143.8
137.9
143.4
128.4
130.3
133.7
137.3
153.0
157.1
108.2
151.9
153.9
136.1
102.9
166.0
69.0
23.2
68.8
23.1
68.6
23.0
68.3
22.9
147.2 147.4
144.2 144.3
138.1 138.2
143.8 143.8
128.9 129.1
131.1 130.9
133.6 133.0
137.8 137.7
153.5 153.4
157.3 157.4
107.8 105.3
152.4 152.9
154.4 155.0
136.9 137.5
102.4 100.6
166.4 167.0
68.1
22.9
68.0
22.8
May
163.4 164.1 164.6 164.8 165.1
152.5 153.3 153.8 154.0 1542
126.1 125.8 125.6 125.4 125.9
170.6 171.5 172.8 173.8 173.6
219.3 220.9 221.4 222.0 222.6
186.6 187.7 188.0 188.3 188.6
147.7
144.6
138.4
144.1
129.4
130.8
133.3
137.8
153.7
157.6
105.3
153.2
155.3
137.7
101.5
167.4
147.4
144.6
138.4
144.0
128.5
129.0
132.4
137.4
154.0
157.6
104.2
153.3
155.1
137.1
99.4
167.5
147.9
145.0
139.0
144.6
128.3
128.4
132.0
137.4
155.2
158.6
103.6
154.0
155.8
137.1
98.0
168.5
67.9
22.8
67.9
22.8
67.7
22.7
148.5 149.0
145.5 145.9
139.4 139.9
145.0 145.5
128.8 129.5
129.0 129.9
132.0 131.9
137.7 138.2
155.8 156.1
159.3 159.7
103.1 102.5
154.6 155.2
156.6 157.3
137.9 138.8
97.3 96.8
169.3 169.9
67.4
22.6
67.2
22.6
149.5
146.5
140.4
146.0
130.2
130.7
132.9
139.1
156.4
160.0
103.3
155.7
157.7
139.3
98.7
170.3
149.9
146.9
140.7
146.3
130.9
131.8
135.1
139.6
156.7
160.2
106.0
155.7
157.8
139.1
103.1
170.5
67.0
22.5
66.8
22.4
32.
Consumer Price Index: U.S. city average and available local area data: all items
(1982-84 = 100, unless otherwise indicated)
Urban Wage Earners
All Urban Consumers
Area'
Pricing
schedule2
1994
Apr.
U.S. city average................
May
Jan.
Feb.
Mar.
Apr.
May
Apr.
May
Jan.
Feb.
Mar.
Apr.
May
144.7
144.9
147.8
148.3
148.7
149.3
149.6
M 147.4
147.5
150.3
150.9
151.4
151.9
152.2
154.4
154.2
157.1
157.6
158.0
158.3
158.5
151.8
151.7
154.8
155.2
155.5
155.8
156.1
M 155.0
154.7
157.7
158.3
158.7
159.0
159.2
151.4
151.1
154.3
154.8
155.1
155.4
155.7
M 153.3
152.8
155.4
155.7
155.9
156.3
156.4
151.1
150.8
153.3
153.7
153.9
154.2
154.3
153.9
139.8
154.2
140.2
157.4
143.0
157.6
143.6
158.1
144.2
158.6
145.0
158.8
145.2
Region and area size3
Northeast urban..................
Size A - More than
1,200,000 .........................
Size B - 500,000 to
1,200,000 .........................
Size C - 50,000 to
500,000 ...........................
North Central urban .............
Size A - More than
1,200,000 .........................
Size B - 360,000 to
1,200,000 .........................
Size C - 50,000 to
360,000 ...........................
Size D - Nonmetro
politan (less
than 50,0000 ....................
South urban........................
Size A - More than
1,200,000 .........................
Size B - 450,000 to
1,200,000 .........................
Size C - 50,000 to
450,000 ...........................
Size D - Nonmetro
politan (less
than 50,000) .....................
West urban.........................
Size A - More than
1,250,000 .........................
Size C - 50,000 to
330 000
Size classes:
A (12/86-100).................
B.....................................
C ....................................
D ....................................
M
M 152.6
M 142.9
152.7
143.3
155.7
146.1
156.0
146.7
156.6 157.0
147.3 148.1
157.1
148.3
M 144.1
144.5
147.3
148.0
148.5
149.0
149.0
140.3
140.7
143.5
144.2
144.7
145.3
145.2
M
142.2
142.0
144.4
145.2
146.1
146.9
147.3
138.5
138.4
140.9 141.8
142.6
143.4
143.9
M 143.7
144.4
147.4
147.7
148.3
149.5
150.0
141.2
141.9
144.9
145.2
145.6
146.9
147.5
M 137.9
M 143.8
138.8
144.3
141.5
146.7
142.3
147.4
142.7
148.0
143.9
148.4
144.6
148.8
136.4
142.2
137.3
142.8
139.8
145.3
140.4
145.9
141.0
146.5
142.2
147.0
142.9
147.4
M 144.4
144.7
146.6
147.3
148.0
148.3
148.7
142.4
142.8
144.8
145.4
146.1
146.4
147.1
M
146.3
148.9
149.6
150.4
150.9
150.8
141.8
142.8
145.6
146.3
146.9
147.4
147.4
147.8
145.5
M 142.9
143.1
145.7
146.2
146.6
147.3
147.6
142.6
142.8
145.7
146.1
146.5
147.3
M 141.3
M 148.9
142.3
148.8
145.2
152.0
146.1
152.4
146.6
152.8
147.1
153.2
148.0
153.5
141.4
145.9
142.5
146.0
145.6
149.2
146.4
149.4
146.7
149.8
147.3
150.3
148.2
150.6
M
150.4
150.4
152.9
153.1
153.6 154.0
154.2
145.8
146.0
148.5
148.7
149.1
149.6
149.7
M
148.6
147.8
154.1
155.1
155.2
155.9
156.4
146.3
145.7
151.4
152.2
152.2
152.8
153.8
M 133.9
M 146.8
M 145.8
M 142.1
133.9
147.0
146.0
143.0
136.2
149.9
149.3
145.9
136.7 137.2
150.5 151.1
149.8 150.2
146.6 147.1
137.5
151.6
151.0
147.7
137.7 132.7 132.9
151.8 144.1 144.4
151.4 144.9 145.2
148.5 141.4 142.3
135.3
147.3
148.6
145.2
135.7
147.9
149.0
145.8
136.2 136.6 136.8
148.5 148.9 149.1
149.3 150.2 150.7
146.3 147.0 147.9
147.9
147.6
151.8
152.3
152.6
153.1
153.0
143.3
143.1
147.1
147.5
147.8
148.3
148.2
M 152.0
151.4
154.3
154.5
154.6
154.7
155.1
146.6
146.2
149.0
149.2
149.3
149.5
149.8
M 157.7
M 153.1
157.3
153.2
159.9
156.6
160.3
157.8
160.9
158.0
161.4
157.8
161.8
157.8
153.9 153.6
152.6 152.7
156.3
156.4
156.6
157.5
157.1
157.5
157.5
157.4
158.0
157.4
M 148.0
148.3
150.3
150.5
151.1
151.5
151.3
145.6
146.1
148.2
148.3
148.9
149.4
149.0
149.1
156.9
139.7
146.6
143.9
152.4
_
149.4
156.5
139.9
146.8
144.2
152.3
-
144.5
143.6
137.6
142.6
Selected local areas
Chicago, IL-Northwestern IN ...
Los Angeles-Long
Beach, Anaheim, CA..........
New York, NYNortheastern NJ .................
Philadelphia, PA-NJ..............
San FranciscoOakland, CA.......................
M
Miami, FL...........................
St. Louis, MO-IL..................
Washington, DC-MD-VA .......
1
1
1
1
1
1
Dallas-Ft. Worth, TX.............
Detroit, Ml..........................
Houston, TX .......................
Pittsburgh, PA ....................
2
2
2
2
Boston, MA ........................
1995
1994
1995
_
_
_
-
140.3
142.6
136.8
143.9
145.8 148.7
153.6 158.0
143.7 146.6
143.3 147.3
140.0 142.9
151.4 153.8
_
_
-
-
_
_
_
143.3
147.3
139.3
147.3
150.3
158.4
147.3
148.7
144.5
155.1
_
"
_
145.0
148.1
138.0
148.9
150.4
157.7
147.4
148.6
144.6
154.7
-
~
_
-
139.3
137.9
136.2
137.4
144.9
152.2
136.1
141.2
139.2
149.2
147.7
157.0
139.0
145.3
142.3
151.2
-
~
_
“
142.7
142.7
138.9
141.1
"
“
"
'
1 Area definitions are those established by the Office of Manage
ment and Budget in 1983, except for Boston-Lawrence-Salem, MA-NH,
Area (excludes Monroe County); and Milwaukee, Wl, Area (includes
only the Milwaukee MSA). Definitions do not include revisions made
since 1983. Excludes farms and the military.
2 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.
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
3 Regions are defined as the four Census regions.
- Data not available.
NOTE: Local area CPI indexes are byproducts of the national CPI
program. Because each local index is a small subset of the national in
dex, it has a smaller sample size and is, therefore, subject to substan
tially more sampling and other measurement error than the national in
dex. As a result, local area indexes show greater volatility than the na
tional index, although their long-term trends are quite similar. Therefore,
the Bureau of Labor Statistics strongly urges users to consider adopting
the national average CPI for use in escalator clauses.
M onthly Labor Review
August 1995
117
Current Labor Statistics: Price Data
33.
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 and upkeep:
Index..................................
Percent change.............................
Transportation:
Index........................................
Percent change...........................
Medical care:
Index...................................
Percent change...........................
Entertainment:
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...........................................
M onthly Labor Review
Digitized for118
FRASER
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
August 1995
1986
1987
1988
1989
1990
1991
1992
1993
1994
109.6
1.9
113.6
3.6
118.3
4.1
124.0
4.8
130.7
5.4
136.2
4.2
140.3
3.0
144.5
3.0
148.2
2.6
109.1
3.3
113.5
4.0
118.2
4.1
124.9
5.7
132.1
5.8
136.8
3.6
138.7
1.4
141.6
2.1
144.9
2.3
110.9
3.0
114.2
3.0
118.5
3.8
123.0
3.8
128.5
4.5
133.6
4.0
137.5
2.9
141.2
2.7
144.8
2.5
105.9
.9
110.6
4.4
115.4
4.3
118.6
2.8
124.1
4.6
128.7
3.7
131.9
2.5
133.7
1.4
133.4
-.2
102.3
-3.9
105.4
3.0
108.7
3.1
114.1
5.0
120.5
5.6
123.8
2.7
126.5
2.2
130.4
3.1
134.3
3.0
122.0
7.5
130.1
6.6
138.6
6.5
149.3
7.7
162.8
9.0
177.0
8.7
190.1
7.4
201.4
5.9
211.0
4.8
111.6
3.4
115.3
3.3
120.3
4.3
126.5
5.2
132.4
4.7
138.4
4.5
142.3
2.8
145.8
2.5
150.1
2.9
121.4
6.0
128.5 .
5.8
137.0
6.6
147.7
7.8
159.0
7.7
171.6
7.9
183.3
6.8
192.9
5.2
198.5
2.9
108.6
1.6
112.5
3.6
117.0
4.0
122.6
4.8
129.0
5.2
134.3
4.1
138.2
2.9
142.1
2.8
145.6
2.5
34.
Producer Price Indexes, by stage of processing
(1982 = 100)
1993
Finished g o o d s ..............................................
Finished consumer goods .....................
Finished consumer foods....................
Finished consumer goods excluding
foods ..............................................
Nondurable goods less food .............
Durable goods ................................
Capital equipment................................
Intermediate materials, supplies, and
com ponents...................................................
1994
1995
1994
Annual average
Grouping
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
126.9
128.3
128.3
126.9
128.5
128.5
127.6
128.5
128.5
128.0
127.9
127.9
124.7
125.7
125.7
125.5
126.8
126.8
125.6
125.9
125.9
126.0
126.2
126.2
126.5
126.6
126.6
125.6
126.3
126.3
125.8
126.1
126.1
126.1
126.9
126.9
126.2
128.6
128.6
126.6
127.9
127.9
121.7
117.6
128.0
78.0
121.6
116.2
130.9
77.0
122.0
116.9
130.8
78.3
122.5
117.5
130.9
79.6
123.4
118.7
131.0
81.4
122.2
117.8
129.2
79.6
122.0
116.3
132.1
77.1
122.3
116.7
132.1
77.7
121.8
115.9
132.2
75.9
122.4
116.7
132.6
76.6
122.6
116.9
132.6
76.6
122.7
117.1
132.4
76.4
123.8
118.7
132.4
78.8
124.7
120.0
132.4
80.4
116.2
118.5
118.2
118.7
119.5
120.1
120.0
120.9
121.1
122.5
123.3
123.7
124.7
125.3
Materials and components for
manufacturing ....................................
Materials for food manufacturing..........
Materials for nondurable manufacturing .
Materials for durable manufacturing......
Components for manufacturing............
118.9
115.6
115.5
119.1
123.0
122.1
118.5
119.2
125.2
124.3
121.2
118.0
117.1
124.2
124.2
121.7
116.2
118.1
125.1
124.4
122.5
117.8
119.7
126.0
124.3
123.7
118.5
122.3
127.4
124.5
124.5
116.8
124.3
128.5
124.6
125.5
118.0
125.4
130.6
124.8
126.2
117.5
126.7
131.8
124.9
128.1
117.8
129.7
134.6
125.7
129.1
118.5
131.5
136.1
125.9
129.5
119.0
132.4
136.5
125.9
130.6
117.1
135.7
136.8
126.2
130.8
116.5
136.5
136.5
126.3
Materials and components for
construction........................................
Processed fuels and lubricants..............
Containers...........................................
Supplies..............................................
84.6
123.8
135.8
125.0
83.0
127.1
137.1
127.0
84.2
126.3
137.1
126.9
85.8
126.7
137.1
126.9
87.3
127.3
137.2
126.9
86.5
128.3
136.4
127.2
83.0
129.2
137.8
127.5
83.4
130.2
137.8
127.9
82.2
130.9
138.1
128.4
82.2
132.6
138.7
129.5
82.4
133.6
139.0
129.8
82.3
134.1
139.1
130.4
83.9
135.2
139.4
131.2
85.6
135.5
139.7
131.3
102.4
108.4
76.7
101.8
106.5
72.1
103.2
107.8
75.2
102.2
103.6
75.3
101.9
101.8
75.6
99.7
101.3
71.3
98.2
98.9
70.2
99.1
100.4
69.3
100.5
101.6
69.9
101.5
102.2
69.8
102.7
104.0
69.8
102.3
103.2
69.2
103.9
101.9
72.9
103.5
99.5
74.1
124.4
78.0
132.9
133.5
135.8
125.1
77.0
134.2
134.2
137.1
125.4
78.3
133.9
133.8
137.1
125.8
79.6
134.0
133.9
137.1
126.4
81.4
134.2
134.1
137.2
125.3
79.6
133.6
133.6
136.4
125.6
77.1
134.5
134.4
137.8
125.8
77.7
134.7
134.7
137.8
125.5
75.9
135.4
135.5
138.1
126.2
76.6
135.7
135.6
138.7
126.4
76.6
136.0
135.9
139.0
126.4
76.4
136.1
136.1
139.1
127.3
78.8
136.3
136.3
139.4
128.0
80.4
136.3
136.3
139.7
138.5
139.0
138.9
138.9
139.0
138.2
139.6
139.7
140.0
140.5
140.8
141.0
141.3
141.7
147.0
147.4
148.2
Crude materials for further processing ...
Foodstuffs and feedstuffs ....................
Crude nonfood materials......................
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......
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
146.1
144.4
144.3
144.2
144.4
144.6
144.7
144.8
145.2
145.9
146.3
116.4
112.7
84.6
123.2
118.7
114.8
83.0
126.3
118.3
115.5
84.2
125.6
119.0
113.4
85.8
125.9
119.8
113.6
87.3
126.5
120.4
113.9
86.5
127.5
120.4
112.2
83.0
128.2
121.3
112.1
83.4
129.1
121.6
111.5
82.2
129.7
123.0
111.8
82.2
131.4
123.9
111.8
82.4
132.4
124.3
112.7
82.3
132.9
125.4
111.7
83.9
133.8
126.0
110.7
85.6
134.0
123.8
127.1
126.3
126.7
127.3
128.3
129.2
130.2
130.9
132.6
133.6
134.1
135.2
135.5
76.7
116.3
140.2
72.1
119.3
156.2
75.2
119.1
152.4
75.3
117.0
155.6
75.6
116.4
157.9
71.3
116.4
159.2
70.2
114.6
159.3
69.3
117.0
164.1
69.9
119.1
168.4
69.8
121.0
174.1
69.8
123.1
177.0
69.2
122.9
178.3
72.9
122.6
180.7
74.1
120.6
179.8
M onthly Labor Review
August 1995
119
Current Labor Statistics;
35.
Price D ata
Producer price indexes for the net output of major industry groups
(December 1984=100 unless otherwise indicated)
Annual
average
SIC
Industry
1993
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 ................
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 ...............
Printing, publishing, and allied
industries..........................
Chemicals and allied products.................
Petroleum refining and related products .
Rubber and miscellaneous plastic products
Leather and leather products ..................
Stone, clay, glass, and concrete products ..
Primary metal industries ..............
Fabricated metal products, except
machinery and transportation
equipment ....................................
Machinery, except electrical....................
Electrical and electronic machinery,
equipment, and supplies.......................
Transportation equipment......................
Measuring and controlling instruments;
photographic, medical, optical goods;
watches, clocks...................................
Miscellaneous manufacturing industries
(12/85=100)....................................
1994
June
1994
July
Aug.
Sept.
1995
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
10
12
13
76.4
69.7
93.3
76.2
73.3
81.4
93.2
71.1
74.9
81.4
92.0
73.5
74.3
84.9
92.1
72.4
75.0
84.4
92.7
73.3
72.4
87.6
94.3
69.2
71.0
88.3
95.0
67.1
70.5
91.1
94.9
66.2
72.0
94.2
92.0
68.6
72.1
101.9
88.4
68.7
71.4
99.0
88.5
67.9
70.9
101.8
91.5
66.4
73.5
105.0
94.4
69.4
74.3
99.1
92.1
71.2
14
118.8
120.5
120.5
120.5
120.4
120.5
120.7
120.8
120.9
122.4
123.3
123.3
123.1
123.1
119.1
20 118.7
21 218.0
22 113.6
120.7
120.1
187.8
113.6
120.4
119.8
187.7
113.5
120.9 121.5
119.7 120.1
187.7 187.7
113.6 113.8
121.1
119.9
187.9
113.8
121.5
119.6
187.6
113.9
121.9
119.6
188.1
114.2
121.7
119.4
187.9
114.3
122.6
120.2
188.1
114.7
123.0 123.2
120.9 121.0
188.8 190.6
115.5 115.7
124.0 124.5
120.2 120.2
190.8 195.3
116.0 116.6
23
119.2
119.7
119.5
119.8
119.7
119.7
119.8
119.7
119.8
120.0
120.1
120.3
120.6
120.5
24
25
26
148.3
125.4
120.2
154.4
129.7
123.7
153.7
130.1
121.6
152.7
130.2
122.1
153.3
130.1
123.3
154.1
130.3
125.5
153.9
130.5
128.2
155.9
130.9
130.4
155.5
131.0
132.8
155.7
131.5
136.0
155.5
131.9
138.8
155.7
132.1
140.8
155.0
132.5
143.7
154.6
132.9
145.6
27
28
29
30
31
32
33
145.6
127.2
77.6
115.4
129.0
115.4
111.4
149.7
130.0
74.8
117.1
130.6
119.6
117.0
149.2 149.4
128.4 129.2
74.7 78.0
116.4 116.7
130.1 130.3
119.8 120.1
116.0 117.0
149.6 150.3 150.8 151.7 152.4
130.3 132.0 133.6 134.4 136.1
82.5 79.5 76.2 77.8 73.5
117.0 117.9 118.8 119.5 120.1
130.6 131.3 131.7 132.1 132.5
120.4 120.7 121.1 121.4 121.6
117.5 118.7 119.7 121.7 122.9
154.7
138.4
74.3
121.3
133.3
122.4
126.6
155.2
140.3
74.7
121.4
133.8
122.8
128.2
156.0
141.0
74.3
122.4
133.9
123.6
129.1
157.0
143.3
80.6
123.1
134.1
124.6
129.4
157.4
145.0
84.4
123.2
134.4
124.8
129.1
34
118.2
120.3
120.0
120.3
120.6
121.8
122.6
123.8
124.2
124.6
124.7
35
116.8
117.5
117.5
117.6
117.6
117.7
117.7
117.7
117.8
118.3
118.8
118.9
119.0
119.0
36
37
112.0
126.3
112.7
130.1
112.7
129.9
112.8
130.1
112.7
130.1
112.6
128.2
112.6
131.5
112.6
131.2
112.7
131.6
113.1
132.2
113.4
132.2
113.1
131.9
113.1
132.0
113.4
131.8
38
120.8
122.1
122.1
122.3
122.2
122.0
122.3
122.6
122.6
122.9
123.1
123.4
123.7
123.6
39
121.5
123.3
123.3
123.5
123.5
123.6
123.6
123.8
124.0
125.0
125.1
125.2
125.5
125.6
42
43
44
45
46
119.8
99.7
105.6
96.6
101.9
119.8
100.0
108.5
102.6
101.9
119.8
99.1
109.1
101.0
102.1
119.8
99.5
109.0
102.3
102.2 102.3
119.8 119.8
100.1 100.3
109.0 108.5
102.9 103.0
102.7
119.8
102.9
108.3
103.7
102.7
119.8
101.4
108.1
106.5
102.9
119.8
101.6
107.9
107.0
103.1
132.1
102.6
108.1
110.9
104.1
132.1
102.6
109.7
110.9
104.4
132.1
102.6
110.7
110.9
104.6 104.5
132.1 132.1
101.9 102.2
110.1 113.6
110.9 110.9
120.8
121.2
121.6
Service industries:
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 (12/86=100)
- Data not available.
36.
Annual data: Producer Price Indexes, by stage of processing
(1982=100)
index
1986
1987
1988
1989
1990
1991
1992
1993
1994
103.2
107.3
63.0
110.6
105.4
109.5
61.8
113.3
108.0
112.6
59.8
117.0
113.6
118.7
65.7
122.1
119.2
124.4
75.0
126.6
121.7
124.1
78.1
131.1
123.2
123.3
77.8
134.2
124.7
125.7
78.0
135.8
125.5
126.8
77.0
137.1
99.1
102.2
72.6
104.9
101.5
105.3
73.0
107.8
107.1
113.2
70.9
115.2
112.0
118.1
76.1
120.2
114.5
118.7
85.5
120.9
114.4
118.1
85.1
121.4
114.7
117.9
84.3
122.0
116.2
118.9
84.6
123.8
118.5
122.1
83.0
127.1
87.7
93.2
71.8
103.1
93.7
96.2
75.0
115.7
96.0
106.1
67.7
133.0
103.1
111.2
75.9
137.9
108.9
113.1
85.9
136.3
101.2
105.5
80.4
128.2
100.4
105.1
78.8
128.4
102.4
108.4
76.7
140.2
101.8
106.5
72.1
156.2
Finished goods:
Total ...........................................................
Foods ......................................................
Energy.....................................................
Other.......................................................
Intermediate materials, supplies, and
components:
Total ...........................
Foods .......................
Energy............................
Other .......................
Crude materials for further processing:
Total .............................
Foods
Energy .............
Other ....................
120FRASER
M onthly Labor Review
Digitized for
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
August 1995
37.
U.S. export price indexes by Standard International Trade Classification
(1990 = 100, unless otherwise indicated)
Category
Food and live anim als....................................................... ,..............................
Meat and meat preparations............................................................
Cereals and cereal preparations......................................................
Vegetables, fruit, and nuts, prepared fresh or dry...............................
Crude materials, Inedible, except fu e ls .......................................................
Hides, skins, and furskins, raw.........................................................
Oilseeds and oleaginous fruits ........................................................
Crude rubber (including synthetic and reclaimed) ...............................
Cork and wood .............................................................................
Pulp and waste paper.....................................................................
Textile fibers and their waste ..........................................................
Crude fertilizers and crude minerals.................................................
Metalliferous ores and metal scrap ..................................................
1995
1994
SITC
Rev. 3
June
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
0
01
04
05
103.9
107.3
101.8
109.6
102.7
105.3
95.7
116.7
102.6
105.9
93.7
117.5
102.4
107.7
96.1
109.6
103.9
108.8
99.6
106.6
105.2
112.4
100.8
109.2
106.7
109.0
103.9
113.3
105.7
109.3
102.8
109.9
106.6
108.7
104.6
109.2
108.3
112.4
103.1
116.8
111.2
113.6
106.7
122.5
2
21
22
23
24
25
26
27
28
108.1
94.4
112.9
96.1
149.4
94.6
105.0
95.6
91.2
109.7
97.9
104.0
99.3
149.6
109.6
102.7
95.4
95.9
109.4
101.0
96.0
100.8
149.9
110.5
102.1
95.8
98.7
108.9
103.9
96.2
99.3
149.1
105.0
101.8
96.2
100.2
108.9
107.2
87.4
102.0
149.0
108.6
100.2
95.4
104.3
112.7
109.9
89.5
104.5
151.0
118.5
103.8
96.4
108.9
116.8
110.4
91.9
104.7
151.5
126.8
110.5
96.4
116.5
120.4
111.2
91.9
109.6
154.6
135.5
116.2
97.5
119.9
124.3
110.7
92.0
115.8
157.8
145.9
122.8
97.2
124.4
127.4
109.6
93.7
117.0
157.3
155.8
132.9
98.4
124.7
130.2
108.3
96.5
121.1
159.4
169.6
131.0
98.5
125.0
Coal, coke, and briquettes..............................................................
Petroleum, petroleum products, and related
materials...................................................................................
3
32
87.4
93.9
89.5
93.4
91.0
93.1
87.6
93.3
87.5
93.6
88.2
93.9
89.3
94.1
89.3
94.0
89.4
94.7
88.9
94.7
90.5
96.0
33
80.3
84.2
87.0
81.1
80.6
81.1
82.8
82.8
82.4
81.8
83.6
Animal and vegetable oils, fats, and w a x e s ...............................................
4
110.0
107.4
109.0
116.2
118.1
119.1
132.1
134.7
124.2
121.8
116.1
Chemicals and related products, n.e.s..........................................................
5
54
55
57
58
59
99.0
108.4
109.2
106.5
99.5
108.7
100.0
107.7
109.5
109.8
99.8
108.5
101.5
107.9
109.4
113.8
100.2
108.9
103.8
107.9
109.7
121.5
101.4
109.0
106.6
107.6
109.5
129.5
104.6
109.2
108.1
107.5
109.7
132.5
104.2
109.7
109.2
107.5
109.4
134.0
104.8
110.9
112.4
107.5
109.7
137.0
105.7
113.1
113.8
107.7
110.1
138.6
106.0
114.3
115.1
108.0
110.4
141.5
106.5
113.1
116.3
108.1
110.4
143.3
108.1
114.3
6
62
104.4
109.2
105.3
109.0
106.1
109.3
106.6
110.2
108.0
110.7
109.3
110.3
110.9
110.5
112.1
111.6
113.1
112.6
113.8
114.6
115.1
114.0
64
66
68
96.2
107.3
92.5
98.5
107.3
95.6
100.3
107.4
97.6
101.8
107.6
98.7
105.9
107.6
102.5
108.2
107.4
107.1
111.0
108.6
111.4
115.6
108.6
113.8
117.1
108.5
116.1
118.5
109.3
115.2
123.7
109.3
116.2
7
71
72
104.1
112.8
109.8
104.1
113.1
109.4
103.8
113.5
109.3
103.7
113.7
109.9
103.7
113.6
109.9
103.8
114.5
109.9
103.7
114.6
109.9
104.0
115.1
110.6
104.2
115.3
111.1
104.2
114.4
111.6
104.3
114.5
112.1
74
75
110.1
81.0
110.1
80.8
110.3
78.8
110.5
78.8
110.5
78.5
110.5
78.4
110.5
78.1
111.2
77.6
111.8
77.2
111.8
76.9
111.9
77.0
76
77
78
107.3
103.2
106.3
107.5
103.0
106.5
107.3
103.1
106.5
106.8
101.8
106.6
106.7
101.9
107.2
106.7
101.7
107.2
106.4
101.5
107.3
107.1
101.8
107.4
107.1
101.5
107.7
106.4
102.3
107.8
105.9
102.5
107.8
87
111.6
111.9
111.9
112.5
112.2
113.1
112.6
113.5
113.4
113.2
113.0
Mineral fuels, lubricants, and related p rodu cts.........................................
Medicinal and pharmaceutical products............................................
Essential oils; polishing and cleaning preparations.............................
Plastics in primary forms (12/92—100) ............................................
Plastics in nonprimary forms (12/92—100).......................................
Chemical materials and products, n.e.s..............................................
Manufactured goods classified chiefly by
m aterials.............................................................................................................
Rubber manufactures, n.e.s..............................................................
Paper, paperboard, and articles of paper, pulp,
and paperboard............................................................................
Nonmetallic mineral manufactures, n.e.s............................................
Nonferrous metals.........................................................................
Machinery and transport equ ipm ent............................................................
Power generating machinery and equipment .....................................
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 ...............................................................................
Professional, scientific, and controlling
instruments and ap p aratu s........................................................................
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
M onthly Labor Review
August 1995
121
Current Labor Statistics:
38.
Price D a ta
U.S. import price indexes by Standard international Trade Classification
(1990=100, unless otherwise indicated)
SITC
Rev.3
Category
Food and live anim als...................................
Meat and meat preparations.....................
Fish and crustaceans, mollusks, and other
aquatic invertebrates......................
Cereals and cereal preparations.................
Vegetables and fruit, prepared fresh or dried ...............
Sugars, sugar preparations, and honey........................
Coffee, tea. cocoa, spices, and manufactures
thereof .................................
Beverages and to b a c c o ..........................................
Beverages..........................................
Crude materials, Inedible, except fu e ls .........................
Crude rubber (including synthetic and reclaimed)...................
Cork and wood ...........................
Pulp and waste paper......................
Crude fertilizers...................................
Metalliferous ores and metal scrap.......................
Crude animal and vegetable materials, n.e.s....................................
Mineral fuels, lubricants, and related produ cts.........................
Petroleum, petroleum products, and related
materials....................................
Gas, natural and manufactured.......................................
Electrical energy...................................
Animal and vegetable oils, fats, and w a x e s .......................................
Chemicals and related products, n.e.s....................................................
Inorganic chemicals.......................................
Dyeing, tanning, and coloring materials ..........................................
Medicinal and pharmaceutical products.......................................
Essential oils; polishing and cleaning preparations...........................
Fertilizers ........................................
Plastics in primary forms (12/92=100)................................
Plastics in nonprimary forms (12/92=100)............................
Chemical materials and products, n.e.s..................................
Manufactured goods classified chiefly by material .................................
Rubber manufactures, n.e.s..............................................
Paper, paperboard, and articles of paper pulp,
paper, or paperboard ............................................
Nonmetallic mineral manufactures, n.e.s......................................
Nonferrous metals.....................................................
Manufactures of metals, n.e.s....................................................
Machinery and transport equipment ..................................................
Machinery specialized for particular industries.................................
General industrial machinery and equipment, 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 ..................................................................
Footwear...........................................................
Photographic apparatus, equipment, and supplies,
and optical goods, n.e.s.............................................................
M onthly Labor Review
122
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
August 1995
1994
1995
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
0
01
118.0
90.7
118.8
91.9
120.6
91.0
118.4
90.9
118.7
91.7
120.1
90.3
116.9
89.7
120.6
88.6
116.0
86.6
117.9
85.1
03
04
05
06
123.6
101.7
99.9
98.8
123.5
100.5
100.1
96.8
126.1
102.5
99.4
97.1
126.5
101.9
100.6
96.7
127.9
101.9
112.6
97.2
125.7
101.6
120.3
98.3
125.6
101.5
110.0
98.8
127.7
102.0
114.4
98.1
127.0
93.3
104.1
99.6
126.0
99.4
111.6
98.4
07
195.9
202.2
212.0
194.5
172.3
172.2
168.6
183.7
176.6
178.1
1
11
113.6
113.1
113.4
113.5
113.6
113.6
113.7
113.8
113.5
113.6
114.0
114.2
113.4
113.6
114.4
114.5
115.0
114.7
114.6
114.7
2
23
24
25
27
28
29
107.2
119.6
154.8
76.7
82.4
90.2
118.6
108.5
121.0
155.4
80.1
82.3
92.3
118.3
110.4
134.0
151.3
86.4
86.0
92.8
117.4
113.9
135.7
157.2
90.0
86.1
94.3
126.6
114.6
143.8
149.6
90.7
86.6
97.2
139.2
118.9
159.8
152.7
97.4
87.9
98.6
142.8
121.6
164.8
150.0
97.4
87.9
101.1
166.3
121.3
165.6
143.3
104.7
89.6
106.6
140.1
123.1
170.4
141.1
108.1
91.8
105.8
154.7
123.5
167.3
139.2
109.5
97.2
105.8
160.9
3
79.2
73.5
73.9
76.9
75.3
76.0
77.8
79.1
82.3
84.9
33
34
35
78.6
86.9
92.4
72.6
87.4
88.8
73.1
86.0
86.2
76.1
87.5
83.3
74.5
88.3
83.5
75.4
84.8
82.3
77.5
81.7
79.9
79.0
79.1
78.0
82.4
79.2
77.4
85.0
81.4
81.1
4
136.9
140.0
141.6
144.1
155.0
152.2
145.4
151.8
153.6
157.3
5
52
53
54
55
56
57
58
59
103.9
100.7
102.7
120.3
110.7
101.0
103.1
99.4
103.1
105.7
102.7
102.5
119.7
110.5
102.1
101.6
102.8
105.2
106.6
105.6
102.9
120.2
111.8
105.0
101.4
102.1
103.1
107.8
106.8
103.2
121.4
112.7
107.0
102.1
105.8
103.4
108.8
107.6
102.9
120.5
113.4
107.2
102.9
107.1
103.7
109.1
108.5
102.4
120.2
114.5
108.2
107.3
110.0
102.6
110.1
109.4
103.3
120.7
115.3
109.7
107.3
112.8
103.4
110.8
113.1
106.4
121.4
116.8
112.0
106.8
115.5
103.8
111.2
112.2
110.9
124.6
120.1
113.1
109.0
116.5
105.0
113.3
113.2
109.1
128.9
124.1
112.8
110.3
119.9
105.7
6
62
102.4
102.2
103.0
101.5
103.9
102.5
105.4
102.6
106.4
102.3
107.4
102.4
108.8
102.1
109.2
102.8
110.6
103.7
112.0
105.2
64
66
68
69
97.9
108.9
90.0
105.7
99.4
109.8
91.0
106.0
99.2
109.6
95.6
106.2
101.3
109.9
99.1
107.0
105.2
110.5
103.1
106.4
108.6
110.4
105.6
106.3
109.9
110.7
110.8
107.0
114.3
110.8
106.1
108.5
119.4
111.1
105.6
110.0
125.2
111.3
106.0
110.6
7
72
107.4
111.5
107.4
111.5
108.1
112.0
108.2
112.8
108.0
112.5
107.9
112.3
108.2
113.2
108.5
114.0
109.5
116.0
110.2
117.1
74
75
110.5
86.0
110.3
86.0
110.9
85.7
111.6
84.5
111.6
84.8
112.1
84.7
112.8
84.6
113.0
84.0
115.8
84.2
116.5
84.1
76
77
78
97.8
106.8
113.4
97.5
106.6
113.5
97.6
106.9
115.0
97.7
106.7
115.3
97.7
106.5
115.1
97.4
106.4
115.0
97.6
106.6
115.3
97.7
106.9
115.8
98.8
107.6
116.3
99.8
108.9
116.8
85
101.0
101.0
101.0
101.3
101.1
100.7
101.0
101.1
101.5
101.7
88
110.6
110.8
111.1
110.8
110.6
109.9
110.7
111.0
113.4
115.6
39.
U.S. export price indexes by end-use category
(1990 = 100 unless otherwise indicated)
1995
1994
Category
Aug.
Sept.
Oct.
Nov.
Jan.
Dec.
Apr.
Mar.
Feb.
May
ALL CO M M O DITIES...............................................................................
103.6
103.8
104.4
105.1
105.8
106.7
107.3
107.9
108.9
109.2
Foods, feeds, and beverages ................................................
Agricultural foods, feeds, and beverages..............................
Nonagricultural (fish, beverages) food
products.........................................................................
101.1
100.1
101.3
100.3
101.5
100.1
102.9
101.5
104.7
103.4
103.8
102.5
104.5
102.8
106.0
103.9
108.7
106.8
109.5
107.7
108.2
107.9
112.1
112.8
113.0
113.5
117.1
122.1
123.3
122.6
Industrial supplies and materials............................................
103.5
104.3
106.0
107.9
109.9
112.5
114.1
115.3
117.1
117.8
Agricultural industrial supplies
and materials .................................................................
105.7
107.1
107.7
109.7
114.4
117.7
118.7
122.0
120.6
120.3
92.9
90.3
90.0
90.6
91.4
91.5
91.6
91.0
92.7
94.1
114.2
153.3
115.5
153.4
117.9
153.5
119.0
151.0
Fuels and lubricants ..........................................................
Nonagricultural supplies and materials,
excluding fuel and building materials..................................
Selected building materials.................................................
104.9
147.3
107.1
148.6
109.2
149.7
103.7
103.6
103.7
103.6
103.9
104.0
104.2
104.6
104.7
106.6
100.8
106.7
100.6
106.8
100.8
106.4
100.6
106.9
100.9
107.0
100.9
107.2
101.0
108.1
101.4
107.9
101.5
106.6
106.7
107.2
107.2
107.3
107.4
107.7
107.4
107.4
107.5
Consumer goods, excluding automotive..................................
Nondurables, manufactured................................................
Durables, manufactured.....................................................
Nonmanufactured consumer goods......................................
107.9
109.9
106.0
99.3
108.1
110.1
106.3
98.4
108.2
110.1
106.5
99.3
108.3
110.2
106.6
98.9
108.2
110.0
106.3
100.7
108.3
110.3
106.3
-
108.8
110.9
106.9
-
109.0
111.3
106.9
99.9
109.3
111.6
107.2
.0
109.5
111.8
107.3
.0
Agricultural commodities.......................................................
Nonagricultural commodities.................................................
101.2
104.0
101.7
104.2
101.6
104.9
103.2
105.5
105.7
106.0
105.6
107.0
106.1
107.7
107.7
108.1
109.7
108.9
110.3
109.2
101.2
147.4
102.6
147.2
Capital goods......................................................................
Electric and electrical generating
equipment................................... ..................................
Nonelectrical machinery.....................................................
103.7
106.5
101.0
Automotive vehicles, parts, and engines.................................
112.2
151.4
- Data not available.
40.
U.S. import price indexes by end-use category
(1990 = 100)
1995
1994
Category
Aug.
Sept.
Oct.
Nov.
Jan.
Dec.
Feb.
Mar.
Apr.
May
ALL CO M M O DITIES...............................................................................
103.3
102.8
103.5
104.2
104.1
104.4
105.1
105.7
106.7
107.8
Foods, feeds, and beverages ................................................
Agricultural foods, feeds, and beverages ..............................
Nonagricultural (fish, beverages) food
products.........................................................................
119.0
117.2
120.0
118.5
121.8
120.2
120.1
117.7
120.2
117.6
121.1
119.4
118.7
116.2
121.9
119.9
118.8
115.7
120.2
118.0
123.2
123.5
125.3
125.7
126.7
125.1
125.0
126.7
126.3
125.5
Industrial supplies and materials............................................
92.5
90.6
91.5
93.8
93.7
94.8
96.6
97.7
99.8
101.7
Fuels and lubricants ............................................................
Petroleum and petroleum products ......................................
80.0
78.1
74.5
72.2
74.8
72.8
77.7
75.8
76.1
74.2
77.0
75.1
78.7
77.1
80.3
78.6
83.5
81.9
86.1
84.4
Paper and paper base stocks................................................
Materials assiciated with nondurable supplies
and materials .................................................................
Selected building materials............................... ....................
Unfinished metals associated with durable goods....................
Nonmetals associated with durable goods ..............................
90.9
93.0
94.7
96.8
100.1
104.7
107.2
112.2
117.1
121.3
104.6
128.4
93.9
98.7
106.4
128.6
95.3
98.0
107.5
126.5
98.1
100.4
109.4
129.8
100.1
100.5
110.3
125.7
102.5
100.7
111.5
125.7
103.8
100.8
112.7
125.2
107.5
101.2
113.3
123.1
106.2
103.0
113.8
122.4
106.8
104.4
115.3
122.0
106.7
107.5
105.1
109.2
103.7
105.2
109.6
103.8
106.3
110.9
104.9
107.2
112.2
105.8
Capital goods......................................................................
Electric and electrical generating equipment.........................
Nonelectrical machinery.....................................................
Transportation equipment, excluding motor
vehicles and spacecraft (12/92 = 100) .............................
Automotive vehicles, parts and engines..................................
104.9
107.7
103.7
104.8
107.4
103.7
105.1
107.7
103.9
105.0
108.3
103.7
104.9
108.1
103.6
104.7
107.9
103.4
104.7
111.5
105.2
111.6
105.7
112.9
105.8
113.2
105.3
113.0
-
-
-
-
-
112.9
113.2
113.6
114.3
115.0
Consumer goods, excluding automotives................................
Nondurables, manufactured................................................
Durables, manufactured .....................................................
Nonmanufactured consumer goods......................................
105.9
105.8
105.5
110.0
106.0
106.0
105.6
110.3
106.2
106.2
105.6
110.6
106.4
106.5
105.6
112.0
106.4
106.4
105.6
113.4
106.3
106.1
105.6
114.0
106.8
106.4
106.0
117.2
106.8
106.9
106.2
112.1
107.3
107.1
106.6
114.1
107.9
107.7
107.4
114.8
- Data not available.
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
M onthly Labor Review
August 1995
123
Current Labor Statistics:
41.
Price a n d Productivity D ata
U.S. international price indexes for selected categories of services
(1990 = 100 unless otherwise indicated))
1995
1994
1993
Category
Mar.
June
Sept.
Mar.
Dec.
Sept.
June
Air freight (inbound) .....................................................
Air freight (outbound)....................................................
100.1
97.3
106.4
96.6
106.6
95.6
106.1
96.4
105.9
96.5
108.1
96.2
Air passenger fares (U.S. carriers) .................................
Air passenger fares (foreign carriers)..............................
Ocean liner freight (inbound).........................................
109.8
108.0
104.0
117.2
115.7
103.5
119.0
117.0
103.3
111.4
107.2
102.1
113.1
108.1
103.4
119.7
114.6
106.3
42.
Mar.
Dec.
108.6
96.2
110.4
97.3
115.4
98.1
121.4
118.1
106.2
113.8
110.0
106.6
116.1
113.8
106.6
Indexes of productivity, hourly compensation, and unit costs, quarterly data seasonally adjusted
(1982 = 100)
Quarterly Indexes
Item
1992
1994
1993
III
IV
115.8
156.0
106.8
134.7
145.8
138.3
116.8
157.7
107.1
135.1
150.2
140.1
116.2
158.7
107.0
136.6
149.5
140.8
113.9
154.7
105.9
135.8
147.1
139.5
115.0
156.4
106.2
136.1
152.1
141.2
119.1
151.5
103.7
124.9
127.2
119.0
171.0
128.8
127.7
127.6
148.3
101.6
116.3
I
III
IV
116.3
159.9
107.0
137.5
149.6
141.4
117.0
160.6
107.0
137.3
150.5
141.6
118.4
161.3
106.6
136.2
154.0
142.1
118.9
163.3
107.4
137.3
153.4
142.6
114.3
157.2
105.9
137.4
151.5
142.0
114.5
158.1
105.8
138.1
151.8
142.5
115.3
158.7
105.7
137.7
153.6
142.8
116.5
159.3
105.3
136.8
156.3
143.1
120.6
153.1
104.0
123.8
127.0
115.7
191.2
129.9
127.9
119.9
153.9
103.7
125.0
128.3
116.8
183.7
129.4
128.7
121.2
154.4
103.3
124.1
127.3
115.8
199.4
131.5
128.7
122.2
154.8
103.1
123.6
126.7
115.8
202.5
132.1
128.5
129.1
150.7
102.3
116.8
130.8
149.9
101.0
114.6
131.3
151.7
101.5
115.5
132.1
152.5
101.6
115.4
II
1995
III
IV
118.5
163.6
106.9
138.1
155.6
143.8
119.5
164.9
106.8
138.0
157.8
144.5
120.7
166.4
107.2
137.8
159.0
144.8
121.4
168.0
107.4
138.4
159.5
145.3
117.0
161.2
106.0
137.8
155.5
143.5
116.6
161.8
105.7
138.8
158.3
145.1
117.3
162.9
105.5
138.8
160.9
145.9
118.6
164.4
105.9
138.7
161.8
146.1
119.4
166.2
106.2
139.2
162.3
146.7
123.4
155.0
102.5
122.6
125.7
114.8
220.9
134.8
128.7
124.0
156.5
102.9
123.5
126.2
116.6
218.2
135.7
129.4
123.8
156.8
102.4
123.4
126.7
115.2
228.7
136.6
129.9
124.3
157.9
102.3
124.0
127.1
116.2
228.8
137.4
130.5
125.3
159.1
102.5
123.8
127.0
115.9
230.3
137.4
130.4
125.9
160.6
102.7
124.3
127.6
116.1
224.9
136.6
130.5
133.6
153.3
101.4
114.7
135.4
154.3
101.4
113.9
136.8
153.6
100.3
112.2
138.0
154.5
100.0
111.9
139.3
155.9
100.4
112.0
140.4
157.7
100.8
112.3
I
II
I
Business:
Output per hour of all persons.........................
Compensation per hour...................................
Real compensation per hour...........................
Unit labor costs .............................................
Unit nonlabor payments..................................
Implicit price deflator ......................................
Nonfarm business:
Output per hour of all persons.........................
Compensation per hour...................................
Real compensation per hour...........................
Unit labor costs .............................................
Unit nonlabor payments ..................................
Implicit price deflator ......................................
Nonfinancial corporations:
Output per hour of all employees.....................
Compensation per hour...................................
Real compensation per hour...........................
Total unit costs..............................................
Unit labor costs ...........................................
Unit nonlabor costs......................................
Unit profits....................................................
Unit nonlabor payments..................................
Implicit price deflator......................................
Manufacturing:
Output per hour of all persons.........................
Compensation per hour...................................
Real compensation per hour...........................
Unit labor costs.............................................
Digitized for124
FRASER
M onthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
August 1995
43.
Annual indexes of multifactor productivity and related measures, selected years
(1987=100)
Item
1960
1970
1973
1980
1986
1987
1988
1989
1990
1991
1992
1993
Private business:
Productivity:
Output per hour of all persons.......................
Output per unit of capital services..................
Multifactor productivity........................
Output............................................
Inputs:
Labor input................
Capital services ............................
Combined units of labor and capital input.......
Capital per hour of all persons.........................
53.5
116.0
70.5
37.8
74.8
115.1
87.2
57.4
83.0
120.1
95.3
67.9
89.1
105.8
96.0
79.9
99.6
99.7
99.8
96.7
100.0
100.0
100.0
100.0
100.9
101.4
100.5
104.3
101.0
101.3
100.3
107.0
101.9
99.8
100.0
107.9
102.9
96.8
99.0
106.5
105.9
97.9
100.5
109.3
106.6
98.8
101.1
112.5
66.7
32.6
53.4
46.3
74.2
49.8
65.7
64.9
78.7
56.6
71.1
69.2
86.8
75.5
83.1
84.2
96.8
97.0
96.8
99.8
100.0
100.0
100.0
100.0
104.2
102.9
103.7
99.6
107.2
105.6
106.7
99.7
107.8
108.2
107.8
102.1
106.5
110.0
107.5
106.1
107.5
111.6
108.6
107.9
110.1
113.8
57.7
122.6
74.9
37.4
77.3
120.5
89.9
57.4
85.6
125.3
98.1
68.3
90.6
108.2
97.7
80.2
99.8
100.0
100.0
96.7
100.0
100.0
100.0
100.0
100.9
101.3
100.5
104.5
100.7
100.9
99.9
107.1
101.3
99.1
99.4
107.8
102.5
96.0
98.5
106.4
105.1
96.8
99.6
108.9
105.9
97.8
100.3
112.4
61.4
30.5
49.7
47.1
72.0
47.7
63.8
64.0
76.9
54.5
69.4
68.3
85.7
74.2
82.0
83.8
96.6
96.7
96.6
99.8
100.0
100.0
100.0
100.0
104.4
103.2
103.9
99.6
107.6
106.1
107.1
99.9
108.3
108.8
108.4
102.3
106.8
110.8
107.9
106.6
108.0
112.6
109.2
108.5
110.9
115.0
-
-
Private nonfarm business:
Productivity:
Output per hour of all persons .......................
Output per unit of capital services..................
Multifactor productivity...............................
Output....................................
Inputs:
Labor input...................................................
Capital services ................................
Combined units of labor and capital input.......
Capital per hour of all persons.........................
- Data not available.
NOTE: Productivity and output in this table have not been revised for
44.
-
-
consistency with the December 1991 comprehensive revisions to the
National Income and Product Accounts.
Annual indexes of productivity, hourly compensation, unit costs, and prices, selected years
(1982 = 100)
Item
1960
1970
1973
1983
1985
1987
1988
1989
1990
1991
1992
1993
1994
Output per hour of all persons.........................
Compensation per hour...................................
Real compensation per hour...........................
Unit labor costs .....................
Unit nonlabor payments ..................................
Implicit price deflator ......................................
65.6
21.1
68.8
32.2
33.6
32.6
87.0
36.7
91.3
42.2
42.7
42.4
95.1
45.1
98.1
47.5
52.1
49.0
102.3
103.8
100.6
101.5
107.5
103.4
106.3
113.2
101.5
106.5
120.8
111.2
109.6
123.1
104.6
112.3
125.5
116.6
110.7
128.5
104.8
116.0
130.6
120.8
109.9
133.0
103.5
121.0
136.6
126.1
110.7
140.6
103.8
127.1
139.8
131.2
112.1
147.4
104.4
131.5
144.9
135.9
115.5
154.9
106.6
134.2
148.3
138.8
117.0
160.1
106.9
136.9
150.9
141.5
119.7
165.1
107.5
137.9
156.3
143.9
69.9
22.2
72.4
31.8
33.3
32.3
88.5
37.0
92.0
41.8
43.0
42.2
96.4
45.4
98.7
47.1
49.6
47.9
102.5
104.0
100.8
101.5
109.2
104.0
105.6
112.8
101.1
106.8
121.6
111.6
108.6
122.5
104.1
112.8
126.6
117.2
109.6
127.7
104.2
116.5
131.8
121.4
108.6
132.0
102.7
121.5
137.1
126.5
109.1
139.2
102.8
127.6
140.6
131.8
110.7
146.2
103.6
132.1
146.5
136.7
113.7
153.7
105.7
135.2
149.7
139.9
115.2
158.3
105.7
137.5
153.4
142.6
117.7
163.1
106.2
138.6
159.1
145.2
75.3
23.6
77.0
29.5
31.4
24.8
75.1
34.2
32.3
90.3
38.4
95.4
40.5
42.5
35.5
69.5
41.9
42.3
95.0
46.6
101.2
46.5
49.0
40.2
87.9
49.2
49.1
103.8
103.4
100.2
99.5
99.6
99.3
135.9
106.2
101.8
106.5
112.0
100.4
103.7
105.2
100.1
168.1
112.9
107.7
111.2
120.9
102.7
107.0
108.8
102.5
172.1
115.6
111.0
113.3
125.9
102.7
109.8
111.1
106.4
183.5
120.9
114.3
111.5
130.2
101.3
115.7
116.8
112.9
168.5
123.3
119.0
112.7
137.1
101.3
120.1
121.7
116.3
167.5
125.9
123.1
115.0
143.8
101.9
123.7
125.0
120.5
164.7
128.8
126.3
118.5
150.4
103.5
124.4
126.9
118.0
177.2
129.1
127.7
121.8
154.6
103.3
123.8
127.0
115.8
201.9
132.0
128.6
124.8
158.2
103.0
123.7
126.7
116.0
226.5
136.8
130.0
102.2
102.7
99.5
100.5
113.5
103.8
106.7
111.3
99.8
104.2
120.1
108.2
116.6
118.4
100.6
101.6
134.5
109.8
119.2
123.1
100.4
103.2
147.4
114.3
119.9
127.9
99.5
106.7
153.3
118.4
122.1
134.7
99.5
110.4
153.7
121.2
124.9
141.9
100.5
113.7
157.0
124.5
127.5
147.9
101.7
116.0
157.0
126.3
132.0
152.0
101.5
115.1
160.8
126.5
137.4
154.5
100.6
112.5
Business:
Nonfarm business:
Output per hour of all persons.........................
Compensation per hour...................................
Real compensation per hour...........................
Unit labor costs ....................................
Unit nonlabor payments .................................
Implicit price deflator ...............................
Nonfinancial corporations:
Output per hour of all employees.....................
Compensation per hour...................................
Real compensation per hour...........................
Total unit costs..............................................
Unit labor costs ...........................................
Unit nonlabor costs......................................
Unit profits.............................................
Unit nonlabor payments ..................................
Implicit price deflator ......................................
Manufacturing:
Output per hour of all persons.........................
Compensation per hour..................................
Real compensation per hour...........................
Unit labor costs .............................................
Unit nonlabor payments ..................................
Implicit price deflator......................................
-
-
-
-
-
-
-
-
-
-
-
-
-
- Data not available.
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
M onthly Labor Review
August 1995
125
Current Labor Statistics:
45.
P roductivity D ata
Annual indexes of output per hour for selected industries
(1987= 100)
Industry
SIC
1973
1979
1985
1986
1987
1988
1989
1990
1991
Iron mining, usable ore ...............................
Copper mining, recoverable metal.................
Coal mining................................................
Crude petroleum and natural gas..................
Nonmetallic minerals, except fuels................
101
102
12
131
14
1 51.7
142.4
1 68.9
1 173.5
1 86.5
1 51.8
148.5
1 54.5
1 110.3
1 92.6
1 76.6
1 93.6
1 85.1
1 83.0
1 95.1
1 79.6
1 109.7
1 92.4
1 90.3
1 95.1
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 103.7
1 109.8
1 110.6
1 101.0
1 102.2
1 99.5
1 107.8
1 116.5
1 98.1
1 101.9
1 90.0
1 104.5
1 118.5
1 97.0
1 108.3
187.0
1 102.9
1 122.1
1 98.1
1 103.6
Meatpacking plants.....................................
Sausages and other prepared meats.............
Poultry dressing and processing...................
Cheese, natural and processed....................
Fluid milk...................................................
Canned fruits and vegetables.......................
Frozen fruits and vegetables........................
Flour and other grain mill products...............
Cereal breakfast foods................................
Rice milling ................................................
Wet corn milling .........................................
2011
2013
2015
2022
2026
2033
2037
2041
2043
2044
2046
165.1
167.2
1 58.0
1 56.6
1 49.5
1 66.0
1 80.1
1 68.5
1 65.6
1 59.3
1 24.1
’ 75.0
192.8
181.7
1 79.8
162.7
1 74.0
’ 86.6
180.5
1 74.2
169.3
1 47.1
1 98.3
1 97.8
1 100.5
1 94.7
1 88.3
193.0
197.0
195.8
1 97.1
1 68.6
1 74.6
1 98.7
1 98.6
1 95.6
1 101.1
1 94.0
1 98.4
1 104.9
195.9
1 98.6
1 72.7
197.3
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 99.5
1 105.6
1 95.9
1 106.4
1 103.9
1 100.2
1 95.1
1 102.0
1 98.6
183.8
1 96.6
1 92.2
1 99.8
1 101.2
1 104.3
’ 106.7
1 92.5
1 98.9
1 101.6
1 96.0
1 98.6
1 103.0
1 92.9
1 93.6
1 107.7
1 101.1
1 108.0
1 96.2
1 92.3
1 107.0
1 102.0
1 106.9
1 104.7
1 94.9
1 90.8
1 114.2
1 98.9
1 110.7
1 103.4
1 98.7
1 107.4
1 105.3
1 101.1
1 100.1
Prepared feeds for animals and fowls...........
Bakery products.........................................
Raw and refined cane sugar........................
Beet sugar ................................................
Malt beverages...........................................
Bottled and canned soft drinks.....................
Fresh or frozen fish and seafood..................
Cigarettes, chewing and smoking tobacco.....
2047,48
2051,52
2061,62
2063
2082
2086
2092
211,3
1 51.6
1 82.3
' 76.7
1 75.9
143.3
149.2
1 93.2
1 79.4
1 66.5
1 83.8
1 96.4
1 78.3
1 63.8
1 64.4
’ 93.8
190.3
1 96.9
1 95.6
196.6
1 73.4
173.7
1 85.2
188.0
193.5
1 95.2
1 100.1
1 96.9
1 80.8
1 85.1
1 91.4
1 91.2
1 95.3
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 101.2
1 93.8
1 97.5
1 95.3
1 99.1
1 109.9
1 99.2
1 106.8
1 103.1
1 93.2
1 97.4
1 87.9
1 102.0
1 119.3
1 92.9
1 107.3
1 106.6
1 96.2
1 100.9
1 91.1
1 110.9
1 126.7
187.1
1 112.9
1 107.2
1 92.9
1 101.3
1 93.4
1 110.1
r 135.1
1 84.8
1 119.2
Cotton and synthetic broadwoven fabrics......
Hosiery .....................................................
Yarn spinning mills......................................
Men’s and boys’ suits and coats..................
221,2
2251,52
2281
231
1 58.1
1 63.2
1 55.9
1 75.6
1 75.6
1 93.3
168.3
1 95.9
193.4
1 100.9
1 89.6
1 106.3
1 99.0
1 102.5
1 93.2
1 103.5
1 100.0
1 100.0
1 100.0
1 100.0
1 100.3
1 107.0
1 98.6
1 102.5
1 104.5
1 108.4
1 103.6
1 101.9
1 109.3
1 106.0
1 106.7
1 98.8
1 115.2
1 111.3
’ 106.3
1 91.3
Sawmills and planing mills, general ..............
Hardwood dimension and flooring.................
Millwork ....................................................
Wood kitchen cabinets................................
Hardwood veneer and plywood ....................
Softwood veneer and plywood .....................
Wood containers........................................
Wood household furniture ...........................
Upholstered household furniture...................
Metal household furniture............................
Mattresses and bedsprings ..........................
Wood office furniture...................................
Office furniture, except wood.......................
Pulp, paper, and paperboard mills.................
Corrugated and solid fiber boxes ..................
Folding paperboard boxes...........................
Paper and plastic bags ...............................
2421
2426
2431
2434
2435
2436
244
2511,17
2512
2514
2515
2521
2522
261,2,3
2653
2657
2673,74
1 68.3
1 84.0
’ 104.2
1 80.5
1 80.2
1 67.7
1 91.2
1 71.9
1 75.6
1 71.6
1 82.5
1 70.6
1 67.1
1 70.3
1 86.4
1 90.7
1 73.3
1 83.0
1 95.4
1 89.1
1 79.6
1 65.6
1 72.9
1 90.4
182.8
172.5
1 86.2
1 117.0
1 76.7
1 77.3
1 87.2
1 90.7
1 94.1
1 93.5
1 95.1
1 97.4
187.1
184.5
188.3
1 99.6
1 93.3
1 98.6
1 98.8
1 77.2
1 99.4
1 96.9
1 87.6
1 99.6
190.0
1 99.7
1 102.3
1 98.8
1 102.2
1 85.2
1 83.2
1 90.4
1 98.7
1 100.2
1 100.6
1 101.7
1 83.1
1 96.2
1 100.6
1 93.3
1 102.8
1 88.5
1 101.8
1 100.0
’ 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 101.7
1 97.4
1 98.3
1 97.8
1 98.3
1 100.3
1 103.4
1 101.0
1 99.8
1 100.6
1 99.2
1 94.8
1 96.0
’ 102.9
1 99.6
1 99.6
1 97.4
1 101.0
1 96.5
1 97.7
1 91.0
’ 97.4
1 102.0
1 108.9
' 100.1
1 101.0
1 100.0
1 105.0
1 94.2
1 99.0
1 103.2
1 97.7
1 101.1
193.6
1 101.5
1 95.4
1 97.9
193.7
1 90.2
1 107.3
1 112.0
1 98.8
1 98.5
1 103.9
1 105.7
1 95.8
1 95.7
1 102.1
1 100.3
1 99.4
1 91.4
1 105.0
1 98.2
1 95.8
1 92.6
1 90.7
1 113.0
' 114.2
1 100.2
1 103.4
1 107.3
1 110.3
1 99.1
1 93.0
1 101.5
1 100.0
1 102.8
1 88.6
Alkalies and chlorine ...................................
Inorganic pigments .....................................
Industrial inorganic chemicals, not
elsewhere classified...................................
Synthetic fibers...........................................
Soaps and detergents.................................
Cosmetics and other toiletries ......................
Paints and allied products...........................
Industrial organic chemicals, not
elsewhere classified...................................
Nitrogenous fertilizers..................................
Phosphatic fertilizers ...................................
Fertilizers, mixing only.................................
Agricultural chemicals, not
elsewhere classified..................................
2812
2816
1 38.4
’ 72.6
1 50.8
1 67.8
1 70.8
1 84.4
1 97.7
1 88.6
1 100.0 1 100.9 1 92.6 1 90.7 1 84.0
1 100.0 1 101.2 1 107.3 1 102.5 1 96.3
2819 pt.
2823,24
2841
2844
285
1 90.6
1 38.4
1 89.1
1 88.6
163.2
1 91.5
1 70.9
1 91.0
1 93.6
1 79.8
187.3
1 79.3
1 91.5
1 90.3
1 96.9
188.6
’ 90.8
1 92.3
1 96.6
1 98.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 96.8
1 102.7
1 103.4
1 105.0
1 103.0
1 104.3
1 103.5
1 110.7
1 101.6
1 106.6
1 106.8
’ 98.3
1 132.1
1 100.8
1 111.4
1 99.0
1 97.1
1 131.7
1 103.4
1 111.2
2869
2873
2874
2875
1 73.1
1 65.4
1 62.4
1 90.5
1 93.0
1 72.7
1 68.3
1 110.9
1 87.8
1 100.7
1 84.2
1 100.8
1 92.3
1 90.5
1 79.6
195.1
1 100.0
1 100.0
1 100.0
1 100.0
1 110.7
1 101.7
1 93.4
1 103.4
1 109.9
1 105.4
1 85.6
1 110.8
1 99.5
1 108.9
1 104.5
1 108.7
1 93.2
1 110.1
1 114.5
1 109.3
2879
1 74.3
1 83.6
1 92.9
1 93.2
1 100.0 1 108.4 1 108.9 1 106.2 1 102.8
Petroleum refining.......................................
Tires and inner tubes ..................................
Rubber and plastics hose and belting...........
Miscellaneous plastic products, not
elsewhere classified..................................
Footwear...................................................
Glass containers ........................................
Cement, hydraulic.......................................
Clay construction products...........................
Clay refractories.........................................
Concrete products ......................................
Ready-mixed concrete ................................
291
301
3052
1 84.0
1 56.0
1 79.3
182.6
1 63.9
1 80.6
1 84.7 1 94.9 1 100.0 1 105.3 1 109.6 1 109.1 1 106.7
1 89.3 1 92.6 1 100.0 1 104.6 1 107.2 1 108.3 1 109.5
1 100.5 1 102.2 1 100.0 1 107.3 1 96.3 1 100.9 1 93.0
308
314
3221
324
3251,53,59
3255
3271,72
3273
1 72.8
1 89.9
1 75.2
1 71.3
1 78.5
180.1
1 92.5
1 99.1
1 74.3
1 94.5
1 83.8
1 68.7
1 79.0
1 93.9
1 91.3
1 96.2
' 88.2
1 99.9
' 93.4
1 91.8
1 94.2
1 94.9
1 99.5
’ 93.7
1 88.9
1 101.7
1 98.5
1 97.1
1 95.5
1 100.8
1 104.4
196.1
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 98.4
1 102.4
1 101.1
' 103.3
1 103.9
1 101.3
1 102.3
1 100.3
' 97.5
1 101.4
1 104.8
1 110.1
1 96.7
1 97.3
1 105.2
1 101.0
1 100.4
1 93.0
1 112.5
1 112.5
1 100.5
1 102.2
1 104.6
1 99.7
1 100.9
1 93.3
1 114.9
1 108.3
1 95.1
1 96.2
1 105.9
196.1
Steel .........................................................
Gray and ductile iron foundries.....................
Steel foundries ...........................................
Primary copper...........................................
Primary aluminum........................................
Copper rolling and drawing ..........................
Aluminum rolling and drawing......................
331
3321
3324,25
3331
3334
3351
3353,54,55
164.2
1 91.3
1 105.8
132.8
1 73.6
1 77.5
1 79.0
165.9
1 92.4
1 104.5
141.1
' 74.7
1 82.0
1 84.3
1 85.8
1 96.9
199.5
1 73.8
1 97.6
186.2
1 85.7
1 89.7
1 99.3
1 104.9
’ 88.7
1 102.7
1 92.3
1 95.8
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 113.4
1 106.8
1 95.3
1 103.7
1 102.2
1 100.0
1 96.9
1 108.5
1 104.1
1 96.6
1 96.8
1 104.6
1 94.1
1 91.2
1 110.5
' 104.1
1 95.9
1 86.3
1 106.3
1 93.9
1 92.4
1 108.1
1 99.3
1 93.2
184.7
1 110.3
’ 96.9
192.0
See footnotes at end of table.
Digitized for126
FRASER
M onthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
August 1995
45. Continued—Annual indexes of output per hour for selected industries
(1987= 100)
Industry
Metal cans.......................................
Hand and edge tools, not elsewhere
classified........................................
Heating equipment, except electric...............
Fabricated structural metal...........................
Metal doors, sash, and trim..........................
Bolts, nuts, rivets, and washers .....................
Automotive stampings...............................
Metal stampings, not elsewhere
classified.................................
SIC
1973
1979
1985
1986
1987
3411
159.2
1 75.2
199.2
1 95.9
1 100.0 1 107.4 1 109.0 1 119.1 1 126.0.
3423
3433
3441
3442
3452
3465
1 108.6
’ 78.0
198.1
1 90.5
1 75.8
1 74.9
1 111.6
' 86.2
186.0
192.6
1 78.9
1 81.4
' 98.8
1 91.9
1 98.6
1 104.8
188.8
194.5
197.1
1 96.2
1 98.8
1 102.0
191.0
1 95.7
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
196.8
1 100.2 1 88.6
1 93.9
1 100.0 1 99.6
3469
1988
1 100.9
1 112.7
198.9
1 102.4
1 97.0
1 104.5
1989
1990
1991
1 102.1
1 103.2
1 94.7
1 101.5
1 93.8
1 104.7
196.4
1 111.2
1 96.8
1 97.0
1 93.7
1 100.8
' 95.0
1 115.4
1 98.3
194.7
1 96.2
1 104.2
198.3
1 95.1
1 96.3
Valves and pipe fittings...............................
Fabricated pipe and fittings..........................
Internal combustion engines, not
elsewhere classified................................
Farm machinery and equipment...................
Lawn and garden equipment........................
Construction machinery...............................
Mining machinery.......................................
Oil and gas field machinery..........................
3491,92,94
3498
3519
3523
3524
3531
3532
3533
1 83.1
1 108.6
1 70.0
1 87.9
1 102.2
1 105.9
186.4
1 112.6
1 83.3
1 91.5
1 89.3
1 100.6
1 92.0
1 101.6
1 82.4
1 92.2
1 93.7
192.3
1 98.5
1 95.7
1 93.2
1 99.1
1 95.1
195.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 105.1
1 112.5
1 97.2
1 107.2
1 102.2
1 99.3
1 110.9
1 123.1
1 91.9
1 109.7
1 107.3
1 104.6
1 105.0
1 130.6
193.4
1 108.9
1 99.0
1 107.4
1 98.9
1 123.6
1 94.5
1 98.2
1 90.7
1 109.2
Metal-cutting machine tools ........................
Metal-forming machine tools........................
Machine tool accessories............................
Pumps and pumping equipment...................
Ball and roller bearings...............................
Air and gas compressors.............................
Refrigeration and heating equipment.............
Carburetors, pistons, rings, and valves..........
3541
3542
3545
3561,94
3562
3563
3585
3592
’ 101.4
1 112.5
1 105.9
1 84.0
1 108.0
1 87.6
1 100.3
1 102.9
1 100.9
1 98.5
1 100.6
191.4
1 110.2
1 86.1
1 98.8
182.0
189.9
1 93.1
1 92.3
1 91.9
1 91.6
1 92.2
1 98.1
1 98.9
1 92.0
1 93.7
1 95.0
192.7
1 94.1
1 96.0
1 95.8
195.7
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
196.1
1 113.8
1 99.3
1 107.3
1 102.4
1 104.1
1 103.5
1 108.8
1 101.2
1 109.9
1 104.6
1 101.4
1 98.2
1 106.1
1 105.7
1 117.1
1 103.1
1 100.6
1 107.4
1 103.4
1 92.1
1 109.2
1 104.6
1 110.9
1 100.2
1 91.9
1 109.2
1 102.6
1 88.3
1 111.8
1 102.6
1 110.7
Transformers, except electronic ...................
Switchgear and switchboard apparatus..........
Motors and generators................................
Household cooking equipment......................
Household refrigerators and freezers ............
Household laundry equipment.......................
Household appliances, not elsewhere
classified.................................................
Electric lamps............................................
Lighting fixtures and equipment....................
Household audio and video equipment..........
Motor vehicles and equipment......................
Aircraft...............................................
Instruments to measure electricity.................
Photographic equipment and supplies...........
3612
3613
3621
3631
3632
3633
1 100.2
188.2
189.0
161.8
1 70.1
1 72.3
1 109.8
1 87.5
189.7
1 79.1
’ 86.8
1 84.7
1 97.0
’ 95.1
1 94.9
1 90.3
1 104.1
1 93.8
1 99.3
1 95.9
1 96.8
1 104.6
1 101.2
1 97.4
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 102.9
1 109.5
1 103.3
1 116.4
1 103.1
1 106.6
1 103.9
1 106.6
1 103.8
1 99.4
1 106.9
1 100.8
1 107.8
1 107.8
1 102.4
1 100.1
1 107.4
1 104.8
1 111.4
1 105.7
1 106.4
1 106.2
1 112.3
1 111.4
1 63.7
161.3
184.1
1 22.3
1 68.7
1 79.2
1 63.7
1 58.9
1 76.1
1 76.1
1 86.2
139.1
1 77.7
198.6
1 70.8
179.0
1 86.3
’ 94.2
1 96.7
1 96.3
1 95.3
1 94.2
1 95.4
1 86.1
1 89.1
1 91.5
1 103.0
1 106.9
1 95.1
1 93.5
1 90.4
1 94.1
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 101.0
1 101.1
1 98.3
1 107.3
1 103.2
1 104.8
1 106.6
1 106.8
1 98.4
1 86.2
1 97.2
1 122.3
1 103.3
1 108.2
1 109.6
1 115.7
1 91.9
1 91.4
1 96.5
1 128.4
1 102.5
1 109.8
1 108.2
1 111.7
1 81.1
1 97.0
1 94.7
1 142.0
1 96.9
1 126.7
1 111.5
1 115.6
Railroad transportation, revenue traffic..........
4011
Bus carriers, class 1 ...................................
411,13,14 pts.
Trucking, except local .................................
4213
Air transportation .......................................
4512,13,22 pts.
Petroleum pipelines ....................................
4612,13
Telephone communications..........................
481
Electric utilities ........................................... 491,493 pt.
Gas utilities................................................ 492,493 pt.
Scrap and waste materials...........................
5093
1 49.3
1 116.8
1 69.5
1 54.3
1 93.2
146.2
1 88.4
1 145.5
-
154.0
1 108.3
183.9
1 75.5
1 96.9
168.7
195.3
1 141.4
1 81.1
1 79.8
1 96.1
1 93.8
1 92.0
1 99.9
1 92.6
1 93.0
1 111.9
1 93.4
1 86.1
1 95.6
1 96.8
1 93.8
1 102.0
1 98.1
1 95.2
1 102.1
' 97.7
' 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 109.3
1 107.9
1 105.2
1 99.5
1 104.8
1 107.8
1 104.9
1 105.5
1 94.3
1 115.4
1 104.6
1 109.4
1 95.1
1 103.2
1 113.4
1 107.7
1 103.6
1 87.8
1 122.6
_
192.2
1 102.5
1 115.1
1 110.0
1 95.0
1 92.2
1 128.1
_
_
1 92.5
1 99.1
1 121.8
1 113.3
1 94.2
1 93.1
Hardware stores.........................................
Department stores......................................
Variety stores ............................................
Grocery stores............................................
Retail bakeries............................................
New and used car dealers ...........................
Auto and home supply stores......................
Gasoline service stations.............................
Men’s and boys’ clothing stores...................
Women’s clothing stores.............................
Family clothing stores .................................
Shoe stores .............................................
Furniture and homefurnishings stores............
Household appliance stores.........................
Radio, television, and computer
stores.....................................................
525
531
533
541
546
551
553
554
561
562
565
566
571
572
183.3
' 60.8
1 148.9
1 109.1
1 125.6
1 85.1
1 71.1
1 59.5
1 77.6
1 58.9
1 76.2
1 81.3
1 83.9
1 59.8
' 97.5
1 74.0
1 123.3
1 106.8
1 112.3
1 86.3
180.1
1 73.7
1 82.3
1 72.8
1 75.4
1 90.9
1 91.0
1 72.9
195.6
192.6
1 129.2
1 105.7
187.6
199.8
194.5
193.5
198.3
199.8
1 103.1
1 97.6
194.8
194.9
1 101.6
1 97.4
1 106.7
1 103.8
1 93.6
1 101.6
1 94.3
1 101.8
1 100.7
1 107.0
1 103.3
1 105.5
1 101.2
1 106.5
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 108.7
199.4
197.3
198.6
1 94.2
1 102.7
1 106.5
1 102.4
1 102.6
1 99.4
1 101.3
1 102.7
1 99.5
1 101.1
1 115.4
1 97.4
1 113.7
1 95.8
1 87.3
1 103.8
1 108.9
1 104.0
1 102.3
1 102.9
1 103.2
1 107.3
1 102.6
1 108.7
1 110.5
1 94.8
1 132.1
1 94.8
1 84.8
1 107.1
1 114.2
1 101.0
1 101.6
1 106.7
1 101.5
1 106.3
1 104.3
1 111.2
1 102.5
1 99.2
1 130.2
1 94.0
1 90.0
1 105.6
1 114.6
1 102.0
1 102.0
1 110.1
1 102.3
1 105.5
1 104.2
1 117.4
573
145.6
1 53.0
189.3
1 94.1
1 100.0 1 122.2 1 122.0 1 131.4 1 146.2
Eating and drinking places ...........................
Drug and proprietary stores..........................
Liquor stores..............................................
Commercial banks......................................
Hotels and motels.......................................
Laundry, cleaning, and garment services.......
Beauty shops.............................................
Automotive repair shops..............................
581
591
592
602
701
721
723
753
1 110.3
1 92.2
1 95.0
181.2
1 102.4
1 110.8
185.9
1 109.3
1 106.6
1 101.8
1 90.2
1 84.1
1 109.7
1 109.9
1 89.4
1 105.0
196.2
1 102.5
1 101.9
194.3
1 101.2
1 103.3
196.1
1 99.4
1 99.3
1 101.6
1 93.8
1 96.2
1 98.9
1 100.8
1 96.9
1 96.1
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 100.0
1 Revised.
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
3639
3641
3645,46,47,48
3651
371
3721
3825
386
1 93.6 1 95.7 1 94.4 1 93.9 1 100.0 1 101.3 1 101.0 1 101.9 1 101.2
1 140.8 1 116.0 1 120.0 1 121.4 1 100.0 1 99.2 1 101.7 1 106.5 1 113.3
1 102.6
1 102.0
1 99.9
1 103.4
1 95.8
1 97.1
1 93.3
1 105.6
1 101.9
1 102.8
1 104.7
1 102.2
1 91.4
1 98.6
1 96.0
1 107.8
1 103.1
1 104.1
1 110.6
1 108.6
1 90.6
1 99.0
1 91.3
1 106.3
1 104.5
1 105.5
1 112.3
1 112.3
1 91.3
1 96.6
1 87.6
1 99.9
- Data not available.
M onthly Labor Review
August 1995
127
Current Labor Statistics:
International Comparisons D ata
46. Unemployment rates, approximating U.S. concepts, in nine countries, quarterly data
seasonally adjusted
Annual average
1993
Country
1993
1994
III
1994
IV
I
II
1995
III
IV
I
United States' ................................
Canada ..........................................
Australia........................................
Japan ............................................
6.8
11.2
10.9
2.5
6.1
10.4
9.7
2.9
6.7
11.4
10.9
2.6
6.5
11.2
10.8
2.8
6.6
11.0
10.4
2.8
6.2
10.6
10.0
2.9
6.0
10.2
9.5
3.0
5.6
9.8
9.1
2.9
5.5
9.7
8.9
3.0
France...........................................
Germany .......................................
Italy2..............................................
Sweden3........................................
United Kingdom ..............................
11.8
5.8
10.3
9.3
10.4
12.3
6.5
11.4
7.8
9.5
12.0
5.9
10.5
9.2
10.5
12.2
6.2
11.0
8.2
10.1
12.3
6.4
11.0
8.2
9.9
12.3
6.5
11.6
7.6
9.7
12.3
6.5
11.1
8.4
9.5
12.3
6.5
11.8
7.2
9.0
12.1
6.4
12.2
7.7
8.7
’ Data for 1994 are not directly comparable with data for
1993 and earlier years. For additional information, see the
box note under “Employment and Unemployment Data” in
the notes to this section.
2 Quarterly rates are for the first month of the quarter.
Break in series beginning in 1993.
3 Break in series beginning in 1993. Data for 1993 on-
128
M onthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
August 1995
ward are not seasonally adjusted.
NOTE: Quarterly figures for France, Germany, and the
United Kingdom are calculated by applying annual adjust
ment factors to current published data and therefore should
be viewed as less precise indicators of unemployment under
U.S. concepts than the annual figures. See “Notes on the
data” for information on breaks in series.
47. Annual data: Employment status of the working-age population, approximating U.S. concepts, 10
countries
(Numbers in thousands)
Employment status and country
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
Civilian labor force
United States' .................................................
Canada ...........................................................
Australia..........................................................
Japan ....................................................
France............................................................
Germany.........................................................
Italy .......................................................
Netherlands.....................................................
Sweden...........................................................
United Kingdom.......................................
115,461 117,834 119,865 121,669 123,869 124,787 125,303 126,982 128,040 131,056
13,123 13,378 13,631 13,900 14,151 14,329 14,408 14,482 14,663 14,832
7,300
7,588
7,758
7,974
8,228
8,444
8,490
8,562
8,619
8,776
58,820 59,410 60,050 60,860 61,920 63,050 64,280 65,040 65,470 65,780
23,620 23,760 23,890 23,980 24,170 24,300 24,490 24,560 24,630 24,890
28,020 28,240 28,390 28,610 28,840 29,410 29,760 30,040 29,960 29,840
21,800 22,290 22,350 22,660 22,530 22,670 22,940 22,910 22,570 22,450
6,250
6,380
6,500
6,530
6,640
6,770
6,870
6,970
7,070
4,418
4,443
4,437
4,494
4,552
4,597
4,591
4,520
4,443
4,418
27,210 27,380 27,720 28,150 28,420 28,540 28,400 28,230 28,150
-
Participation rate2
United States' .................................................
Canada ...........................................................
Australia..........................................................
Japan ........................................................
France............................................................
Germany.........................................................
Italy ....................................................
Netherlands.....................................................
Sweden..................................................
United Kingdom................................................
64.8
65.8
61.6
62.3
56.9
54.7
47.2
55.5
66.9
62.2
65.3
66.3
62.8
62.1
56.9
54.9
47.8
56.0
67.0
62.2
65.6
66.7
63.0
61.9
56.7
55.0
47.6
56.3
66.4
62.6
65.9
67.2
63.3
61.9
56.4
55.1
47.4
56.1
66.9
63.4
66.5
67.5
64.0
62.2
56.1
55.2
47.3
56.5
67.3
63.8
66.4
67.3
64.6
62.6
55.6
55.0
47.2
56.8
67.0
63.9
66.0
66.7
64.1
63.2
55.6
55.4
48.6
57.5
66.6
63.4
66.2
65.5
63.6
63.3
55.6
54.5
48.3
58.6
64.2
62.6
66.3
65.9
63.9
63.4
55.8
55.1
48.5
57.9
65.3
62.8
66.6
65.3
63.9
63.1
55.9
-
48.0
_
63.6
-
Employed
United States' ................................................
Canada ...........................................................
Australia..........................................................
Japan .............................................................
France ............................................................
Germany.........................................................
Italy ................................................................
Netherlands.....................................................
Sweden...........................................................
United Kingdom................................................
107,150 109,597 112,440 114,968 117,342 117,914 116,877 117,598 119,306 123,060
11,742 12,095 12,422 12,819 13,086 13,165 12,916 12,842 13,015 13,292
6,697
6,974
7,129
7,398
7,720
7,859
7,676
7,637
7,680
7,921
57,260 57,740 58,320 59,310 60,500 61,710 62,920 63,620 63,810 63,860
21,150 21,240 21,320 21,520 21,850 22,100 22,140 22,010 21,720 21,830
26,010 26,380 26,590 26,800 27,200 27,950 28,480 28,660 28,220 27,900
20,490 20,610 20,590 20,870 20,770 21,080 21,360 21,230 20,240 19,890
5,650
5,740
5,850
5,920
6,070
6,260
6,380
6,470
6,450
4,293
4,326
4,340
4,410
4,480
4,513
4,447
4,265
4,028
3,992
24,150 24,300 24,860 25,730 26,350 26,580 25,910 25,410 25,220
-
Employment-population ratio3
United States' .................................................
Canada ...........................................................
Australia..........................................................
Japan .............................................................
France ............................................................
Germany.........................................................
Italy ................................................................
Netherlands.....................................................
Sweden...........................................................
United Kingdom................................................
60.1
58.9
56.5
60.6
51.0
50.7
44.4
50.1
65.0
55.2
60.7
59.9
57.7
60.4
50.8
51.3
44.2
50.3
65.2
55.2
61.5
60.8
57.9
60.1
50.6
51.5
43.8
50.7
65.0
56.2
62.3
62.0
58.7
60.4
50.6
51.6
43.7
50.8
65.7
57.9
63.0
62.4
60.1
60.8
50.7
52.0
43.6
51.7
66.2
59.1
62.7
61.9
60.1
61.3
50.5
52.2
43.9
52.5
65.8
59.5
61.6
59.8
57.9
61.8
50.3
53.0
45.3
53.4
64.5
57.8
61.4
58.4
57.0
62.0
50.0
52.6
44.9
53.8
61.7
56.5
61.6
58.2
56.6
61.7
49.0
51.3
43.3
53.4
58.2
56.1
62.5
58.5
57.7
61.3
49.1
42.5
_
57.4
-
8,312
1,381
603
1,560
2,470
2,010
1,310
600
125
3,060
8,237
1,283
613
1,670
2,520
1,860
1,680
640
117
3,080
7,425
1,208
629
1,730
2,570
1,800
1,760
650
97
2,860
6,701
1,082
576
1,550
2,460
1,810
1,790
610
84
2,420
6,528
1,065
508
1,420
2,320
1,640
1,760
570
72
2,070
6,874
1,164
585
1,340
2,200
1,460
1,590
510
84
1,960
8,426
1,492
814
1,360
2,350
1,280
1,580
490
144
2,490
9,384
1,640
925
1,420
2,550
1,380
1,680
500
255
2,820
8,734
1,649
939
1,660
2,910
1,740
2,330
620
415
2,930
7,996
1,541
856
1,920
3,060
1,940
2,560
_
426
-
7.2
10.5
8.3
2.6
10.5
7.2
6.0
9.6
2.8
11.2
7.0
9.6
8.1
2.8
10.6
6.6
7.5
10.0
2.6
11.2
6.2
8.9
8.1
2.9
10.8
6.3
7.9
10.0
2.2
10.3
5.5
7.8
7.2
2.5
10.3
6.3
7.9
9.3
1.9
8.6
5.3
7.5
6.2
2.3
9.6
5.7
7.8
8.6
1.6
7.3
5.5
8.1
6.9
2.1
9.1
5.0
7.0
7.5
1.8
6.9
6.7
10.4
9.6
2.1
9.6
4.3
6.9
7.1
3.1
8.8
7.4
11.3
10.8
2.2
10.4
4.6
7.3
7.2
5.6
10.0
6.8
11.2
10.9
2.5
11.8
5.8
10.3
8.8
9.3
10.4
6.1
10.4
9.7
2.9
12.3
6:5
11.4
_
9.6
9.5
Unemployed
United States' .................................................
Canada ...........................................................
Australia..........................................................
Japan .............................................................
France ............................................................
Germany.........................................................
Italy ................................................................
Netherlands.....................................................
Sweden...........................................................
United Kingdom................................................
Unemployment rate
United States' .................................................
Canada ...........................................................
Australia..........................................................
Japan .............................................................
France ............................................................
Germany.........................................................
Italy ................................................................
Netherlands.....................................................
Sweden...........................................................
United Kingdom................................................
1 Data for 1994 are not directly comparable with data for 1993 and
earlier years. For additional information, see the box note under
“Employment and Unemployment Data” in the notes to this section.
2 Labor force as a percent of the working-age population.
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
3 Employment as a percent of the working-age population.
- Data not available.
NOTE: See “Notes on the data” for information on breaks in series
for Italy and Sweden.
M onthly Labor Review
August 1995
129
Current Labor Statistics:
48.
International Comparisons D ata
Annual indexes of manufacturing productivity and related measures, 12 countries
(1982 = 100)
1960
1970
1973
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
51.6
18.5
24.1
32.4
29.6
37.1
29.1
26.5
46.4
36.1
50.3
76.9
50.3
44.0
57.2
58.6
66.4
54.6
52.9
73.0
69.0
72.1
91.9
64.4
57.4
72.7
69.4
77.9
65.2
67.3
85.4
81.2
86.2
103.5
116.3
107.9
117.5
104.3
103.9
109.0
115.7
115.0
112.2
111.9
112.4
106.7
119.8
114.9
119.6
105.0
107.9
113.4
122.3
118.7
115.8
113.6
116.4
109.5
117.9
113.0
121.4
98.9
109.7
114.2
123.7
120.1
114.7
115.4
120.6
116.6
119.0
122.4
123.8
98.4
111.6
112.7
127.2
120.7
120.4
117.6
126.9
119.2
119.5
129.6
128.9
102.1
119.3
116.7
130.0
124.4
119.5
119.3
133.5
119.9
120.0
138.7
134.5
105.6
125.4
120.5
134.0
128.5
125.3
123.1
138.4
122.1
122.0
149.1
134.1
105.5
127.6
125.6
139.3
130.1
129.3
125.0
140.1
124.9
122.9
156.9
137.0
105.5
128.0
130.1
143.8
131.4
130.3
126.1
145.3
127.5
128.0
156.8
142.2
107.7
130.9
128.0
150.8
132.2
132.5
132.8
152.4
131.6
130.9
157.3
146.4
113.9
132.3
130.0
159.2
133.8
135.3
141.5
159.7
44.1
15.1
37.6
45.4
35.1
51.0
28.0
42.7
56.0
51.8
82.9
78.5
55.1
70.4
75.7
72.7
87.0
58.4
80.3
88.4
91.1
110.5
100.0
71.8
86.3
88.5
87.0
96.4
70.7
91.2
101.3
98.7
121.9
111.3
120.2
113.2
109.9
111.7
98.7
104.6
105.4
107.9
105.0
113.6
105.9
114.0
127.0
121.2
111.8
115.3
99.1
108.4
108.9
111.1
108.8
115.7
108.9
115.2
127.9
117.9
111.9
115.3
99.1
110.1
111.5
113.8
108.8
117.1
110.3
123.5
134.1
126.5
112.3
110.6
98.9
108.1
116.3
115.4
110.8
120.0
115.5
130.0
140.9
138.2
118.0
112.3
104.6
111.5
125.0
119.7
105.5
123.7
123.6
131.2
142.1
149.3
125.0
113.6
110.3
115.4
129.7
125.2
103.8
125.1
129.1
130.6
136.8
160.6
126.5
112.4
112.4
121.7
132.3
129.3
104.5
124.3
128.9
128.2
127.5
170.8
125.9
111.1
110.6
126.2
132.1
129.9
102.3
117.4
121.9
130.1
128.3
167.7
125.8
112.5
109.8
123.3
132.4
129.0
104.2
113.3
121.1
135.4
134.7
160.7
120.5
113.2
106.3
113.8
129.6
125.8
105.9
115.1
122.8
94.1
85.5
81.7
156.2
140.0
118.5
137.2
96.2
160.9
120.9
143.7
164.9
106.5
102.1
109.6
159.9
132.3
123.9
131.1
107.0
152.0
121.1
132.0
153.3
112.6
108.8
111.5
150.3
121.8
125.3
123.7
108.3
135.6
118.7
121.6
141.4
107.6
103.3
104.9
93.6
107.1
95.0
96.0
91.1
93.8
93.5
101.5
94.2
106.8
106.0
105.5
93.5
109.8
91.8
95.6
89.0
93.6
94.0
101.9
93.5
105.2
108.5
104.3
92.2
116.6
90.3
96.4
90.1
94.8
94.8
101.5
91.5
106.0
112.7
103.4
90.7
112.4
88.6
95.9
91.4
95.6
92.0
102.0
91.0
109.0
117.9
106.7
91.5
110.0
87.7
95.6
96.1
96.2
88.3
103.6
92.6
109.4
118.4
107.6
93.0
107.6
88.0
95.7
96.8
97.4
82.9
101.6
93.3
107.0
112.2
107.7
94.3
106.6
88.1
96.9
95.0
99.4
80.9
99.4
92.0
102.6
103.7
108.8
91.9
105.3
86.4
97.0
91.8
98.9
78.5
93.1
83.9
102.0
100.3
106.9
88.4
104.4
83.8
96.3
87.8
97.6
78.6
85.4
79.5
102.9
102.9
102.2
82.3
99.4
80.3
87.6
81.4
94.0
78.3
81.4
76.9
United States................................................................
Canada ........................................................................
Japan ..........................................................................
Belgium........................................................................
Denmark......................................................................
France .........................................................................
Germany......................................................................
Italy .............................................................................
Netherlands..................................................................
Norway ........................................................................
Sweden........................................................................
United Kingdom.............................................................
16.4
6.6
9.1
7.7
7.6
13.5
3.9
8.9
9.9
9.3
7.1
28.7
25.0
23.2
22.3
18.5
34.5
11.6
27.8
24.6
24.4
14.7
35.9
40.7
35.5
34.5
26.2
48.2
17.7
43.4
35.3
34.3
22.6
106.0
111.1
105.8
114.8
113.0
119.6
110.0
134.3
106.6
120.9
119.6
114.6
111.3
116.8
110.1
122.0
120.6
129.6
116.3
150.9
111.5
132.2
131.8
125.1
115.8
121.3
115.6
127.0
123.1
135.1
121.2
157.1
115.4
145.0
142.4
135.4
118.4
125.0
118.6
130.0
134.6
140.0
126.9
166.0
118.8
165.6
151.9
149.8
123.1
130.5
120.6
132.7
139.4
145.4
131.8
172.5
119.5
175.7
161.8
159.4
127.9
135.4
128.2
139.7
147.3
153.2
138.2
189.5
120.1
183.4
179.0
174.7
134.7
143.0
138.3
147.5
156.5
161.3
147.9
210.8
123.3
193.7
197.5
180.6
141.9
151.7
146.2
156.8
162.2
168.3
157.8
233.1
129.2
202.8
215.1
199.4
147.9
158.1
153.0
164.9
167.2
174.1
165.6
249.7
136.6
208.4
225.0
219.7
152.8
159.0
157.1
171.2
171.4
179.8
177.8
266.1
140.5
210.4
221.6
236.1
Unit labor costs: National currency basis
United States................................................................
Canada ........................................................................
Japan ..........................................................................
Belgium........................................................................
Denmark......................................................................
France.........................................................................
Germany......................................................................
Italy.............................................................................
Netherlands..................................................................
Norway........................................................................
Sweden........................................................................
United Kingdom.............................................................
31.9
35.5
38.0
23.8
25.7
36.4
13.5
33.4
21.3
25.8
14.2
37.3
49.7
52.6
39.0
31.5
51.9
21.3
52.7
33.7
35.4
20.4
39.1
63.2
61.8
47.4
37.7
61.9
27.1
64.5
41.4
42.2
26.3
102.4
95.5
98.1
97.7
108.3
115.2
101.0
116.1
92.7
107.8
106.9
101.9
104.2
97.6
95.8
102.0
114.9
120.2
102.6
123.4
93.9
114.2
116.1
107.5
105.8
102.9
102.4
104.7
124.5
123.2
106.2
127.1
96.1
126.4
123.4
112.3
101.6
105.0
96.8
105.0
136.8
125.5
112.6
130.5
98.4
137.5
129.1
118.0
103.2
109.2
93.1
103.0
136.5
121.8
113.0
132.6
96.0
147.1
135.6
119.4
106.7
112.8
92.4
103.8
139.5
122.2
114.6
141.4
93.5
146.3
145.4
126.2
110.4
117.2
92.7
110.0
148.3
126.4
117.8
151.3
94.7
149.8
158.0
128.9
113.7
123.4
93.2
114.4
153.8
131.5
121.3
162.1
98.3
155.6
170.6
137.2
116.0
123.5
97.5
115.9
155.1
133.0
129.4
165.6
103.3
157.3
169.5
144.2
116.1
121.4
99.9
117.0
150.5
135.9
136.8
167.2
105.1
155.5
156.6
147.8
Unit labor costs: U.S. dollar basis
United States................................................................
Canada ........................................................................
Japan ..........................................................................
Belgium........................................................................
Denmark......................................................................
France .........................................................................
Germany......................................................................
Italy .............................................................................
Netherlands..................................................................
Norway ........................................................................
Sweden.......................................................................
United Kingdom............................................................
40.6
24.6
34.9
28.8
34.4
21.2
29.5
23.7
19.3
31.4
22.8
44.1
34.6
48.5
43.4
37.5
34.6
46.0
38.9
30.4
42.8
28.0
48.2
58.1
72.8
65.7
55.9
56.8
63.1
62.0
46.5
60.9
36.8
102.4
91.0
102.9
77.5
87.3
86.7
86.2
89.5
77.2
85.3
81.2
77.9
104.2
88.2
100.1
78.7
90.4
88.0
84.7
87.5
75.6
85.8
84.8
79.8
105.8
91.4
151.5
107.3
128.3
117.0
118.8
115.4
104.8
110.3
108.8
94.3
101.6
97.8
166.8
128.7
166.7
137.3
152.1
136.3
129.8
131.7
127.8
110.7
103.2
109.5
180.9
128.1
169.0
134.5
156.1
137.9
129.8
145.5
138.8
121.6
106.7
117.6
166.7
120.6
159.0
126.0
148.0
139.5
117.7
136.6
141.5
118.3
110.4
124.0
159.3
150.7
200.0
152.7
176.9
170.9
138.9
154.7
167.6
131.6
113.7
132.9
172.5
153.2
200.4
153.2
177.3
176.8
140.3
154.8
177.1
138.7
116.0
126.2
191.6
165.1
214.4
165.3
201.2
182.0
157.0
163.4
182.8
145.7
116.1
116.2
223.9
154.8
193.6
157.8
200.8
143.8
151.0
141.5
126.3
127.0
Item and country
Output per hour
United States................................................................
Canada ........................................................................
Japan ..........................................................................
Belgium........................................................................
Denmark......................................................................
France .........................................................................
Germany......................................................................
Italy .............................................................................
Netherlands..................................................................
Norway ........................................................................
Sweden........................................................................
United Kingdom.............................................................
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......................................................................
Netherlands..................................................................
Norway ........................................................................
Sweden........................................................................
United Kingdom.............................................................
Compensation per hour
- Data not available.
130
M onthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
August 1995
49.
Occupational injury and illness incidence rates by industry,1 United States
Incidence rates per 100 full-time workers3
1985
1986
1987
1988
1989'
1990
1991
1992
19934
PRIVATE SECTOR5
Total cases...............................................................................
Lost workday cases .......................................................................
Lost workdays...............................................................................
7.9
3.6
64.9
7.9
3.6
65.8
8.3
3.8
69.9
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
-
Agriculture, forestry, and fishing5
Total cases................................................................
Lost workday cases.......................................................................
Lost workdays...............................................................................
11.4
5.7
91.3
11.2
5.6
93.6
11.2
5.7
94.1
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
-
Mining
Total cases.................................................................................
Lost workday cases....................................................................
Lost workdays...............................................................................
8.4
4.8
145.3
7.4
4.1
125.9
8.5
4.9
144.0
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
-
15.2
6.8
128.9
15.2
6.9
134.5
14.7
6.8
135.8
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
15.2
6.8
120.4
14.9
6.6
122.7
14.2
6.5
134.0
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
Construction
Total cases...................................................................................
Lost workday cases.......................................................................
Lost workdays...............................................................................
General building contractors:
Total cases...................................................................................
Lost workday cases.......................................................................
Lost workdays...............................................................................
Heavy construction, except building:
Total cases...................................................................................
Lost workday cases.......................................................................
Lost workdays...............................................................................
Special trade contractors:
Total cases...................................................................................
Lost workday cases.......................................................................
Lost workdays...............................................................................
14.5
6.3
127.3
14.7
6.3
132.9
14.5
6.4
139.1
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
15.4
7.0
133.3
15.6
7.2
140.4
15.0
7.1
135.7
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
-
Manufacturing
Total cases...................................................................................
Lost workday cases.......................................................................
Lost workdays...............................................................................
10.4
4.6
80.2
10.6
4.7
85.2
11.9
5.3
95.5
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
-
Durable goods:
Total cases.................................................................................
Lost workday cases ....................................................................
Lost workdays.............................................................................
10.9
4.7
82.0
11.0
4.8
87.1
12.5
5.4
96.8
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
18.5
9.3
171.4
18.9
9.7
177.2
18.9
9.6
176.5
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
15.0
6.3
100.4
15.2
6.3
103.0
15.4
6.7
103.6
16.6
7.3
115.7
14.8
6.6
128.4
14.6
6.5
13.9
6.7
127.8
13.6
6.5
126.0
14.9
7.1
135.8
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
12.6
5.7
113.8
13.6
6.1
125.5
17.0
7.4
145.8
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
-
16.3
6.9
110.1
16.0
6.8
115.5
17.0
7.2
121.9
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
-
10.8
4.2
69.3
10.7
4.2
72.0
11.3
4.4
72.7
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
-
6.4
2.7
45.7
6.4
2.7
49.8
7.2
3.1
55.9
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
-
9.0
3.9
71.6
9.6
4.1
79.1
13.5
5.7
105.7
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
-
5.2
2.2
37.9
5.3
2.3
42.2
5.8
2.4
43.9
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
9.7
4.2
73.2
10.2
4.3
70.9
10.7
4.6
81.5
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
-
9.6
10.0
11.1
11.4
11.6
11.7
11.5
11.3
10.7
Lumber and wood products:
Total cases.................................................................................
Lost workday cases ....................................................................
Lost workdays.............................................................................
Furniture and fixtures:
Total cases.................................................................................
Lost workday cases .....................................................................
Lost workdays.............................................................................
Stone, clay, and glass products:
Total cases.................................................................................
Lost workday cases ....................................................................
Lost workdays.............................................................................
Primary metal industries:
Total cases.................................................................................
Lost workday cases .....................................................................
Lost workdays.............................................................................
Fabricated metal products:
Total cases.................................................................................
Lost workday cases .....................................................................
Lost workdays.............................................................................
Industrial machinery and equipment:
Total cases.................................................................................
Lost workday cases .....................................................................
Lost workdays.............................................................................
Electronic and other electrical equipment:
Total cases.................................................................................
Lost workday cases ....................................................................
Lost workdays.............................................................................
Transportation equipment:
Total cases.................................................................................
Lost workday cases.....................................................................
Lost workdays.............................................................................
Instruments and related products:
Total cases.................................................................................
Lost workday cases .....................................................................
Lost workdays.............................................................................
Miscellaneous manufacturing industries:
Total cases.................................................................................
Lost workday cases .....................................................................
Lost workdays.............................................................................
Nondurable goods:
Total cases.................................................................................
See footnotes at end of table.
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Federal Reserve Bank of St. Louis
16.1
7.2
16.9
7.8
15.9
7.2
-
-
-
M onthly Labor Review
-
-
-
-
-
-
August 1995
131
Current Labor Statistics:
Injury a n d Illness D ata
49. Continued— Occupational injury and illness incidence rates by industry,1 United States
Incidence rates per 100 full-time workers3
Industry and type of case2
1985
Lost workday cases .....................................................................
Lost workdays.............................................................................
Food and kindred products:
Total cases.................................................................................
Lost workday cases .....................................................................
Lost workdays.............................................................................
Tobacco products:
Total cases.................................................................................
Lost workday cases .....................................................................
Lost workdays.............................................................................
Textile mill products:
Total cases.................................................................................
Lost workday cases .....................................................................
Lost workdays.............................................................................
Apparel and other textile products:
Total cases.................................................................................
Lost workday cases .....................................................................
Lost workdays.............................................................................
Paper and allied products:
Total cases.................................................................................
Lost workday cases .....................................................................
Lost workdays.............................................................................
Printing and publishing:
Total cases.................................................................................
Lost workday cases .....................................................................
Lost workdays.............................................................................
Chemicals and allied products:
Total cases.................................................................................
Lost workday cases .....................................................................
Lost workdays.............................................................................
Petroleum and coal products:
Total cases.................................................................................
Lost workday cases .....................................................................
Lost workdays.............................................................................
Rubber and miscellaneous plastics products:
Total cases.................................................................................
Lost workday cases .....................................................................
Lost workdays.............................................................................
Leather and leather products:
Total cases........................... .....................................................
Lost workday cases .....................................................................
Lost workdays.............................................................................
1986
1991
1992
19934
5.4
101.7
5.5
107.8
5.6
116.9
5.5
119.7
5.3
121.8
5.0
16.7
8.1
138.0
16.5
8.0
137.8
17.7
8.6
153.7
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
7.3
3.0
51.7
6.7
2.5
45.6
8.6
2.5
46.4
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
7.5
3.0
57.4
7.8
3.1
59.3
9.0
3.6
65.9
9.6
4.0
78.8
10.3
4.2
81.4
9.6
4.0
85.1
10.0
4.4
88.3
9.9
4.2
87.1
9.7
4.1
6.7
2.6
44.1
6.7
2.7
49.4
7.4
3.1
59.5
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
10.2
4.7
94.6
10.5
4.7
99.5
12.8
5.8
122.3
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
6.3
2.9
49.2
6.5
2.9
50.8
6.7
3.1
55.1
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
6.0
2.8
64.2
5.9
2.7
6.2
2.9
68.2
5.9
2.8
71.2
5.2
2.5
16.2
7.8
151.3
15.1
7.2
150.9
14.5
6.8
153.3
13.9
6.5
12.1
5.4
128.5
12.1
5.5
5.1
2.3
38.8
5.1
2.4
49.9
13.4
6.3
107.4
6.3
2.7
49.4
7.1
3.2
67.5
14.0
6.6
118.2
7.0
3.1
58.8
7.3
3.1
65.9
15.9
7.6
130.8
7.0
3.3
59.0
7.0
3.2
68.4
16.3
8.1
142.9
7.0
3.2
63.4
6.6
3.3
68.1
16.2
8.0
147.2
6.5
3.1
61.6
6.6
3.1
77.3
6.4
3.1
62.4
"
-
■
-
-
"
-
“
-
-
10.3
4.6
88.3
10.5
4.8
83.4
12.4
5.8
114.5
11.4
5.6
128.2
13.6
6.5
130.4
12.1
5.9
152.3
12.5
5.9
140.8
8.6
5.0
107.1
8.2
4.8
102.1
8.4
4.9
108.1
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
7.4
3.2
50.7
7.7
3.3
54.0
7.7
3.4
56.1
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
7.2
3.5
59.8
7.2
3.6
62.5
7.4
3.7
64.0
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
7.5
3.1
47.0
7.8
3.2
50.5
7.8
3.3
52.9
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
“
2.0
.9
15.4
2.0
.9
17.1
2.0
.9
14.3
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
5.4
2.6
45.4
5.3
2.5
43.0
5.5
2.7
45.8
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
Finance, insurance, and real estate
Total cases...................................................................................
Lost workday cases.......................................................................
Lost workdays...............................................................................
Services
Total cases...................................................................................
Lost workday cases.......................................................................
Lost workdays...............................................................................
1 Data for 1989 and subsequent years are based on the S tandard
1987 Edition. For this reason, they are not
strictly comparable with data for the years 1985-88, which were based on the
S tand ard Industrial Classification M anual, 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:
August 1995
1990
5.1
93.5
Total cases...................................................................................
Lost workday cases.......................................................................
Lost workdays...............................................................................
Wholesale trade:
Total cases...................................................................................
Lost workday cases.......................................................................
Lost workdays...............................................................................
Retail trade:
Total cases...................................................................................
Lost workday cases.......................................................................
Lost workdays...............................................................................
M onthly Labor Review'
132
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Federal Reserve Bank of St. Louis
1989’
4.6
82.3
Wholesale and retail trade
Industrial C lassification M anual,
1988
4.4
77.6
Transportation and public utilities
Total cases...................................................................................
Lost workday cases.......................................................................
Lost workdays .............................................................................
1987
"
"
-
-
N = number of injuries and illnesses or lost workdays.
EH = total hours worked by all employees during the calendar year.
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.
- Data not available.
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U.S. Import and Export Price Indexes
August 1
June
August 29
July
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August
Employment situation
August 4
July
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August
October 6
September
August 8
2ndquarter
MLR table
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1; 4-20
Productivity and costs:
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2; 42-45
September 7
2ndquarter
2; 42-45
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August 10
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September 12
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October 12
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September 13
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July
September 13
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