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September 1995
REVIEW
U.S. Department of Labor
In this issue:
Earnings mobility
Intermittent labor force
Security brokers and dealers
Unemployment insurance benefits
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Federal Reserve Bank of St. Louis
Bureau of Labor Statistics
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September 1995
Volume 118, Number 9
Articles
Editor-in-Chief
Deborah P. Klein
Executive Editor
Richard M. Devens, Jr.
Managing Editor
Anna Huffman Hill
Editors
Brian I. Baker
Leslie Brown Joyner
Mary K. Rieg
Stephen Singer
Editorial Assistant
Earnings mobility in the United States, 1967-91
Earnings are less stable for the young, blacks, and less educated workers
than for older, white, and more educated workers
Maury Gittleman and Mary Joyce
3
Effects of intermittent labor force attachment on women's earnings
Women who leave the labor force lose seniority, are less likely
to receive on-the-job training, and their job skills may depreciate
Joyce P. Jacobsen and Laurence M. Levin
14
Employment trends in the security brokers and dealers industry
Over the 1984-93 period, the industry's professional jobs
almost doubled; clerical job growth was weak, due to technological advances
Brett Illyse Graff
20
Trends in unemployment insurance benefits
The share of the unemployed receiving unemployment benefits
has declined slowly since the 1940's, and remains low
Daniel P. McMurrer and Amy B. Chasanov
30
Ernestine Patterson Leary
Production Manager
Dennis L. Rucker
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
Departments
Labor month in review
Technical notes
Industrial relations
Workplace performance
Book reviews
Current labor statistics
2
40
45
49
51
55
Labor month in review
The September Review
Where most studies of earnings distri
bution compare snapshots of the labor
force as it is divided into earnings
classes at particular points in time,
Maury Gittleman and Mary Joyce of the
BLS Division of Special Studies exam
ine the transitions among classes dur
ing the interval between points in time.
One positive finding is that workers in
the bottom quintile of earnings are
slightly more likely to move out of that
class than are those in the top fifth. On
a more somber note, they warn that their
results “do not suggest that mobility
patterns have changed in such a way as
to offset the recent rise in earnings in
equality.”
Joyce P. Jacobsen, professor of eco
nomics at Wesleyan, and Laurence M.
Levin, research associate at Corner
stone Research, calculate the cost of tak
ing an intermission in one’s career in
terms of the difference in wages be
tween women who work continuously
and those who have one or more gaps
in their work history. According to their
calculations, the wage ratio in the first
month of their study was 1.33. This in
dicates that women who had not left the
labor force were earning about a third
again as much as those who had at least
one break. This disparity persisted at
very close to that level throughout the
32 months of data analyzed. Even after
accounting for differences in other in
dividual characteristics, they find that
the difference diminishes, but never dis
appears.
The 9 years ending in 1993 saw ma
jor economic, technological, and regu
latory changes in the way business was
done in the securities brokers and deal
ers industry. Brett Illyse Graff, an
economist in the BLS Division of Occu
pational and Administrative Statistics,
uses the extremely detailed information
available from the Occupational Em
ployment Statistics (OES) survey to trace
the impact of those changes on the staff
ing patterns of the industry. Today’s in
dustry has a far greater share of its
workers in professional and sales jobs
2
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and far fewer in clerical or managerial
positions.
Daniel P. McMurrer and Amy B.
Chasanov draw on their experience as
policy analysts at the Advisory Council
on Unemployment Compensation to
analyze recent developments in unem
ployment insurance programs and their
impact on the ability of the system to
carry out its wage replacement and sta
bilization functions.
Harley Frazis, Michelle Harrison
Ports, and Jay Stewart contribute a tech
nical note on the impact of question
changes prior to the 1994 CPS redesign
on that survey’s measures of educational
attainment. Markley Roberts of the a f l CIO reviews Trade Union Growth and
Decline: An International Study (by
Walter Galensen). Michael H. Cimini
and Charles A. Muhl summarize devel
opments in industrial relations and
Polly A. Phipps analyzes recent find
ings on workplace performance.
Wage flexibility
varies widely
In the June 1995 issue of Labour Eco
nomics, Geraint Johnes and Thomas
Hyclak derive measures of real wage
flexibility for each of the 48 contiguous
States in “The determinants of real
wage flexibility.” These measures are
based on three-stage least squares esti
mates of the coefficient on unemploy
ment in State-specific, expectationsaugmented Phillips curves. According
to Johnes and Hyclack, the five States
with the most flexible wages were North
Dakota, South Dakota, Nebraska, Utah,
and Maryland. The five States with the
most rigid wages were New Mexico,
Connecticut, Delaware, New Jersey, and
New York.
Netsurfing?
On Labor Day, the Bureau hit the
Internet with a new and im proved
World Wide Web site. The BLS Home
Page URL is http ://stats.b ls.g o v /
blshome.html. For on-line help contact:
labstat.helpdesk @bls.gov
September 1995
Shiskin Award
to IRS statistician
The Washington Statistical Society and
the National Association of Business
Economists awarded the 1995 Julius
Shiskin Award to Fritz Scheuren,
former Director of the Statistics of In
come Division of the Internal Revenue
Service. The award committee cited Dr.
Scheuren’s contributions to the con
struction of microeconomic data files,
the statistical use of administrative data
for economic research, and providing
complex data on the American tax sys
tem to other government agencies and
to researchers around the world.
Dr. Martin Fleming, chair of the
Julius Shiskin Award Committee, de
clared “We can be proud that the United
States produces what is without ques
tion the finest database of its kind in the
world, thanks being due in large part to
Fritz’s dedication, talents, and abilities.”
The award is named in honor of the
ninth U.S. Commissioner of Labor Sta
tistics. It is designed to honor original
and important contributions to the de
velopment of economic statistics or in
the use of economic statistics in inter
preting the economy.
Reader survey ‘95
The October issue will carry our tearout reader survey. Your responses last
year were extremely useful, and we hope
to hear from even more of you this time.
When you pick up your Review next
month, please take a few minutes to fill
out and return the short questionnaire.
The October Review
The October Review compares compen
sation in the United States and 29 coun
tries or areas, discusses employment in
Japan, examines new measures of un
employment that take advantage of data
collected in the redesigned CPS, de
scribes the new BLS quarterly produc
tivity measures, reports on productivity
in retail stores, and takes a look at em
ployer-sponsored health benefits.
Earnings Mobility
Earnings mobility
in the United States, 1967-91
The young, the less educated,
and blacks have more instability
in their earnings than do those
who are older, more educated, or white
Maury Gittleman
and
Mary Joyce
Maury Gittleman and
Mary Joyce are econo
mists in the Office of
Publications and Spe
cial Studies, Bureau of
Labor Statistics.
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Federal Reserve Bank of St. Louis
n recent years, the gap between high earn
ers and low earners in the United States has
widened. Information about this phenom
enon is generally reported in relation to a par
ticular point in time. The Census Bureau, for
example, reports on the percentage of families
whose income is below the poverty line during a
particular year and releases annual data on the
share of household income by quintile. While
such statistics reveal important insights into how
individuals are faring economically, they paint
an incomplete picture.
To gain a fuller appreciation of the impact of
poverty, one must understand not only trends in
poverty rates, but also the extent to which a fam
ily that is in poverty in a given year will remain
there in a particular specified period that follows.
In a similar way, those concerned about equity
will want to know not only whether the share of
income going to the top fifth of the income distri
bution is growing or declining, but also whether
there are patterns in the degree to which house
holds move in and out of a given portion of the
income distribution.
To move from the static view of the economy
inherent in most economic data on the income
distribution to a more dynamic perspective, it is
necessary to have information on the mobility of
individuals, families, and households over time—
that is, the extent to which these economic units
change positions in the income distribution over a
given period. What proportion of families in
poverty this year will escape poverty next year?
Are those in the middle class now likely to be there
5 years from now? Do the rich in one year tend to
be the rich in the next, or do individuals from other
income classes move into the top tiers? A study of
I
mobility can provide insights relevant to an
swering important questions such as these. In
addition, the degree of earnings mobility is im
portant not only for developing a more com
prehensive view of the workings of the economy,
but also in such areas as designing pension
schemes or income-contingent student loan
programs, where benefits or repayment respon
sibilities depend on a person’s earnings over his
or her working life and not during a particular
year. Further, mobility patterns contribute to an
understanding of labor markets, as certain patterns
will be consistent with some labor market theories
but not with others.1
This article addresses two important questions
concerning earnings mobility in the United
States. First, how do patterns of earnings mobil
ity differ by sex, age, race, and education? While
many recent studies examine trends in earnings
across demographic groups,2 much less atten
tion has been devoted to the extent to which
those of a given group are able to maintain or
improve their relative economic status from one
year to the next. And, second, how have mobil
ity patterns changed over time? A vast literature
has developed that seeks to document and ex
plain the large increase in earnings inequality
in the United States,3 but little is known about
whether—as the earnings distribution became
more pulled apart—it got harder or easier for
individuals to work their way up the economic
ladder. Trends in mobility have implications
both for the causes of the rise in earnings in
equality and for the extent to which inequities
in earnings in a given year even out over time.
A number of important findings emerge from
this study. First, important differences appear
Monthly Labor Review
September
1995
3
Earnings Mobility
across demographic groups in regard to their mobility within
the overall earnings distribution: women are more likely to
remain in the bottom quintile and less likely to remain in the
top quintile of the overall earnings distribution than are men;
and blacks are more likely than whites to slip out of the top
quintile and to remain in the bottom quintile of the overall
distribution. Second, differences also appear in relative mobility
within various earnings distributions for groups defined by their
demographic characteristics: the young, the less educated, and
blacks have more instability in their earnings than those who
are older, more highly educated, or white. Third, short-term
mobility levels have not undergone major changes over the
time span 1967-91.
Measuring mobility
Before mobility can be measured, a number of methodologi
cal issues must be addressed. First is the choice of the unit
of analysis—that is, whether it is to be families or individu
als.4 Because this article examines the way in which the
labor market distributes rewards and how the process
changes over time, the focus is on individuals. For the same
reason, earnings are emphasized rather than income, as the
latter may include income from property, government pro
grams, and other sources outside of the labor market. If the
goal were to assess changes in the distribution of economic
well-being, the family would probably be the appropriate
choice, because one’s welfare is determined not only by one’s
own income, but also by the income of other household mem
bers.5 In addition, in that instance, it would be advisable to
include as broad a measure of a family’s economic resources
as possible, not just its labor-market earnings.
The article focuses on two different concepts of earnings
mobility. The first is concerned with the positions and move
ments of various demographic groups within the earnings dis
tribution of the entire population. Measures of this type of
mobility seek to provide answers to questions such as the fol
lowing: What proportion of the blacks that are in the top
quintile (top fifth) of the overall earnings distribution in a given
year maintain that position over time? Or, what proportion of
white males in the bottom quintile in a particular year will
have moved to a higher quintile the following year? Such a
concept of mobility highlights differences in various demo
graphic groups’ ability to change or maintain their relative
positions within the overall earnings distribution.
The second type of mobility examines relative earnings
movements within subdistributions defined by demographic
characteristics. For example, it is well known that those with
less education will have lower earnings, on average, than
the more educated. But focusing, say, on high school drop
outs, do the better off within this group tend to be the same
year after year, or is there a substantial reshuffling of eco
4
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Federal Reserve Bank of St. Louis
September
1995
nomic positions? And how does this “churning” in the earn
ings distribution for high school dropouts compare with that
for other groups?
Issues in interpreting findings. A number of important is
sues must be kept in mind in interpreting the results to be pre
sented. Suppose one of the findings is that individuals experi
enced substantial changes in their relative positions within the
overall earnings distribution or within that of a subpopulation.
This can be thought of as evidence of either a high degree of
short-term earnings mobility or a high level of short-term earn
ings instability, depending on one’s perspective. To most ears,
“earnings mobility” sounds like something to be favored on
equity grounds, as it connotes the opportunity to change one’s
relative economic position. The term “earnings instability,” on
the other hand, suggests a negative flip side to this, hinting at
potential difficulties involved in attempting to maintain one’s
economic status. Thus, the normative aspects of the findings
are a matter of interpretation, open to debate about whether the
glass is “half empty” or “half full.”
It is also important to keep in mind the distinction be
tween earnings mobility and earnings growth. The measures
presented in this article of earnings mobility over a given
period are concerned solely with the degree to which indi
viduals shift relative positions within the earnings distribu
tion, not with absolute growth in real earnings levels over
time.6 Thus, by definition, mobility implies that one person’s
upward movement within the earnings distribution is ac
companied by another person’s downward shift.
Data
The analysis to be presented uses March-March matched files
from the Annual Demographic Files of the Current Population
Survey (CPS)7 from 1968 to 1992. The CPS is designed so that
potentially half of the individuals surveyed in a given March
will also be present in the sample in the following March.8 By
linking surveys, one can follow an individual for 2 years and
see how his or her position in the earnings distribution changes
over that period. While earnings mobility is best studied over
as long a time span as possible, there are several important
advantages to using the sequence of 2-year panels made avail
able by linking CPS data. First, the CPS is a nationally repre
sentative data set, so one can follow all age groups over time.9
Second, the samples obtainable from the matched cps's are
generally larger than those from the longitudinal data sets, al
lowing more precise estimates of mobility for various subpopu
lations than is possible using smaller panel data sets. Third, 2year panels can be constructed to cover a lengthy period—
nearly 25 years.
Construction o f samples. From the 25 March CPS'S from
1968 to 1992, it was possible to construct 20 matched
samples.10 Each of these was divided into the following four
main subsamples, using annual wage and salary income as the
measure of economic status in a given year: men with positive
wage and salary income in both years; men working full time,
year round (at least 50 weeks’ work, usually working at least
35 hours per week) in both years; women with positive earnings
in both years; and women working full time, year round in
both years.11 For all samples, the following criteria had to be
met for both years: age between 25 and 59 years; not selfemployed; and not in the top percentile of the earnings
distribution of the appropriate subsample. The trimming of the
top 1 percent of earners is done both because some of the
measures of mobility used in this article are sensitive to outliers
and because it is desirable to eliminate from the sample those
for whom data on earnings have been censored or “top coded.”
For the latter individuals, it is known that their earnings are
above a certain threshold, but it is not known by how much.12
To be included in the group of those with positive wage and
salary income in a given 2-year sample (either men or women;
referred to later as the positive samples), annual earnings
merely had to be nonzero in both years. To be included in the
group of those working full time, year round in both years of
the sample (again, either men or women; referred to later as
the full-time, year-round samples), which implicitly controls
for differences across individuals in hours worked, annual
earnings had to exceed 1,750 (50 weeks times 35 hours) times
one-half the applicable minimum nonfarm hourly wage rate in
both years.
Results are presented for both samples because they repre
sent different aspects of mobility. For the full-time, year-round
samples, the movement within the distributions is due mainly
to relative changes in the rate of pay, while in the positive
samples, changes in hours worked also play a role. In part
because not all changes in hours worked are voluntary, it is
important to assess mobility for both samples.
In addition to these four subsamples, the following samples,
divided along three demographic dimensions, were used:
age—intervals of 25-29,30-39,40-49, and 50-59 years; years
of schooling completed—fewer than 12 years, 12 years, 13-15
years, and 16 or more years; and race—white and black.13
Mobility patterns, 1967-91
Mobility within the overall earnings distribution. To measure
both kinds of mobility defined earlier, appropriate yardsticks
are required.14 For the first type of mobility—movement in
the overall earnings distribution—consider a device known as
a transition matrix. If the overall earnings distribution is
divided into quintiles in year t - 1 and year t, a 5 x 5 matrix can
be calculated wherein each cell (i, j) shows the proportion of
those in quintile i in year t - 1 that are in quintile j in year t.
Table 1 presents a hypothetical example of such a matrix. The
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matrix shows that, of those who are in the second quintile
in year 1, 0.3, or 30 percent, will fall to the bottom quintile
in year 2. The percentages in each row must sum to 1,
because all of the individuals who were in a given quintile
in year 1 must be in some quintile in year 2. By similar
reasoning, the columns must sum to 1 as well. While every
cell is of potential interest, for purposes of discussing
movements within the overall distribution, consider cells
(1,1) and (5, 5)—that is, the percentage of those who start
off in the bottom quintile of the overall earnings distribution
and remain there, and the same measure for the top quintile.
ow do demographic groups differ in terms of their po
sitions and movements within the overall earnings dis
tribution? To answer this question, let us examine the pat
terns of the two sexes and then, separately by sex, of the 10
demographic groups defined by age, years of schooling, and
race. The first two columns of table 2 report the percentage
of each demographic group that was in the first (bottom)
and in the fifth (top) quintile of the overall earnings distri
bution during 1990, and the second two columns show the
percentage of these that remained in those quintiles during
1991. The percentages are given for the positive and the full
time, year-round samples. While the results shown are for
1990-91 only, the basic patterns hold for any pair of years
during the 1967-91 period.
Although differences in mean earnings between men and
women have been declining,15 striking differences remain at
the extremes of the distribution, with women being much
more likely than men to be in the bottom quintile and much
less likely to be in the top quintile. In fact, about the same
percentage of women were in the bottom quintile (30 per
cent) as men were in the top quintile (31 percent) of the
earnings distribution for the positive sample during 1990.
As regards each of the sexes, blacks were much more likely
to be in the lowest quintile, and much less likely to be in the
highest quintile, than whites were. White men were the least
likely to be at the bottom and the most likely to be at the top,
whereas the tendency for black women was just the opposite.
Mobility patterns within the overall distribution also dif
fer by sex and race. In general, the lower a group’s average
earnings, the lower is the likelihood that individuals from
H
Table 1.
Hypothetical transition matrix
Quintile in year t
Quintile in year r - i
1
2
3
4
5
.........................
.........................
.........................
.........................
.........................
1
2
3
0.4
.3
.2
.1
.0
0.2
.3
.2
.1
.2
0.2
.2
.3
.2
.1
Monthly Labor Review
4
5
0.1
.1
.2
.4
.2
0.1
.1
.1
.2
.5
September
1995
5
Earnings Mobility
IU
m iX h
Sex and race differences in mobility within the
overall earnings distribution in 1990-91, using
matched c p s data
Percent in
quintile—
Sex and race
Positive sample
Percent that stay
in quintile—
1
5
1
5
Full sample..............................
20
20
66
74
Sex:
M e n .............................
Women.............................
10
30
31
8
51
72
77
63
Race:
White m en.........................
Black m en ............................
White wom en........................
Black women.........................
8
23
29
31
33
17
9
6
48
57
72
73
78
59
65
44
Full sample.............................
20
20
68
74
Sex:
M e n ..................................
Women..................................
12
30
30
8
58
73
76
64
Race:......................................
White m en...........................
Black m en ........................
White women.......................
Black wom en........................
10
26
29
38
31
17
9
5
56
65
73
73
77
54
66
42
Full-time, yearround sample
that group will stay in the highest quintile, and the greater is
the likelihood that they will stay in the bottom quintile. For
example, women are more likely to stay at the bottom than
men: some 72 percent of women who were in the bottom
quintile of the earnings distribution of the positive sample in
1990 stayed there in 1991, compared with only 51 percent of
men. By contrast, 77 percent of men at the top in 1990 re
mained there in 1991, compared with only 63 percent of
women. Low-earning women appear to be stuck at the bot
tom, even when the labor supply is controlled for by restrict
ing the sample to those who work full time, year round in
both years, which suggests that persistently low hours of
work are not the sole source of these women’s lack of up
ward mobility. It may be that women in the bottom quintiles
are more likely to work in occupations that consistently pay
low wages and have limited promotion potential.
A caveat must be mentioned before continuing with the
findings: even within quintiles, groups will have different
earnings distributions. For example, among those in the bot
tom quintile, men are closer than women, on average, to the
boundary between the first and second quintiles. Thus, even
if men and women have the same increase in earnings from
one year to the next, men will be more likely than women to
move out of the bottom quintile, boosting the meas-ure of
mobility presented for men. Experimentation with other
6
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Federal Reserve Bank of St. Louis
September
1995
measures, however, suggests that the results would be quali
tatively similar even if these intraquintile differences were
taken into account when measuring mobility.
The ability to maintain one’s position at the top of the
overall earnings distribution appears to be more elusive for
blacks than for whites—even for black men relative to white
women. About 65 percent of white women who were in the
top quintile in 1990 were there in 1991, compared with 59
percent of black men and 44 percent of black women. Simi
lar racial differences in the ability to maintain the top eco
nomic, status were also found by Bradley R. Schiller, Greg
Duncan and Saul Hoffman, and Linda Datcher-Loury.16
Datcher-Loury found that high-earning black men and highearning white men differ in their distribution across occupa
tions, which may contribute to their differences in earnings
mobility. High-earning white men were more likely to work
in managerial or professional occupations, in which earn
ings are more stable, whereas high-earning black men were
more likely to be employed in sales and clerical jobs, in which
earnings tend to fluctuate more. Significant differences
across races in movements out of the bottom quintile exist
only for men, with 52 percent of white men leaving the bot
tom quintile, compared with 43 percent of black men. These
general patterns hold for both earnings samples.
able 3 reports differences in mobility within the overall
earnings distributions across age and education groups.
Not surprisingly, younger, less educated workers are more likely
than older, more educated workers to be in the bottom quintile,
and less likely to be in the top quintile, of both earnings distri
butions. The percentage of each age group that remains in the
bottom quintile decreases with age, except for the oldest group,
whose percentage is higher than that of the youngest group.
Similarly, the percentage of each age group that remains in the
top quintile increases with age, also except for the oldest group,
whose percentage is lower than that of the youngest group.
These patterns are consistent with the human capital view of
the pattern of earnings over the life cycle, which suggests that
as a worker ages, earnings rise rapidly at first, then flatten out,
and ultimately begin to fall.17
The percentage of each education group that stays in the
bottom quintile decreases consistently with years of school
ing, and the percentage that stays in the top quintile increases
consistently with years of schooling, indicating that it is
easier for more educated workers to move out of the bottom
and to remain at the top than it is for workers with less edu
cation. These mobility patterns are similar for men and
women within both earnings distributions. The education
mobility patterns are not surprising if one believes that edu
cation represents a perm anent improvement in an in
dividual’s human capital and thus earnings capacity. In that
case, the highly educated workers would be more likely to
T
Table 3.
Age and education differences in mobility within the overall earnings distribution in 1990-91, using m atched CPS data
Full-time, year-round sample
Positive sample
Sex, age,
and
education
Percent that stay
in quintile—
Percent in
quintile—
1
5
1
5
Percent that stay
in quintile—
Percent in
quintile—
1
5
1
5
Men
Age, years:
25-29 ..........................
30-39 ..........................
40-49 ..........................
50-59 ..........................
18
10
6
9
14
28
41
40
53
49
46
57
74
79
79
71
22
13
8
9
12
27
38
38
58
61
50
64
71
77
79
69
Education, years:
Fewer than 1 2 .............
1 2 ................................
13-15 ..........................
16 or m o re..................
23
11
7
5
10
20
34
56
64
47
50
37
50
67
75
86
31
14
8
5
8
19
30
52
65
59
51
49
61
62
75
83
Age, years:
25-29 ..........................
30-39 ..........................
40-49 ..........................
50-59 ..........................
32
30
28
31
6
8
10
8
73
73
69
74
55
63
66
64
34
31
24
36
5
7
11
7
74
72
74
75
46
66
66
63
Education, years:
Fewer than 1 2 .............
1 2 .................................
13-15 ..........................
16 or more..................
55
36
25
15
2
3
7
20
81
71
71
63
10
54
59
69
67
40
25
10
1
4
6
19
85
75
66
57
33
55
58
68
Women
have the necessary skills to reach the top quintile and re
main there. If a less educated worker, on the other hand,
reaches the top quintile, then it is more likely to be due to a
favorable transitory shock that will dissipate with time.
Levels o f mobility within various subdistributions. With re
gard to the second type of mobility examined in this article—
movement within the earnings distribution of a particular de
mographic group—transition matrices are also calculated, ex
cept that in this case an individual is assigned to a quintile for
a pair of years in terms of his or her position in the earnings
distribution for a given demographic group, not for the entire
population. In addition to the proportions that remain in the
top and bottom quintiles, two further measures are calculated.
The first reflects the percentage of people that stay in the same
quintile for both years or, in other words, stay on the diagonal
of the transition matrix. To calculate this measure, it is neces
sary to add up the percentages in the diagonal and then divide
by 5 (because each of the percentages is calculated with a base
that represents one-fifth of the population).
If there is perfect immobility—that is, if every individual
stays in the same quintile—then the measure will equal 1.0,
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because all the diagonal elements will be 1.0 (and all the other
elements 0.0). If, on the other hand, there is perfect mobility—
that is, if an individual’s position in the beginning year has no
impact on his or her position in the ending year—then the
measure will equal 0.2, because all the diagonal elements—
and, in fact, all elements—will equal 0.2. Making the relevant
calculations for the transition matrix in table 1 results in a
value of 0.38 ([0.4 + 0.3 + 0.3 + 0.4 + 0.5J/5) for this measure
of mobility.
An additional measure calculates the percentage of indi
viduals who either stay in the same quintile or move into an
adjacent one—in other words, those who stay on or near the
diagonal of the transition matrix. Under perfect immobility,
this measure will also be 1.0, as everyone stays on the diag
onal. With perfect mobility, it will be 0.52 because there are
13 elements on or adjacent to the diagonal, each of which
would equal 0.2 ([13 x 0.2]/5 = 0.52). As applied to table 1,
the measure equals 0.68.18
The final measure for assessing the extent of mobility
within a given distribution is the correlation coefficient,
which gives a guide to the extent to which individuals main
tain their positions within the earnings distribution. The
Monthly Labor Review
September
1995
7
Earnings Mobility
measure ranges from -1.0 to 1.0, with 1.0 indicating perfect
immobility, 0.0 perfect mobility, and negative values (not
observed in the calculations carried out) some reversal of
positions.
In this section, mobility patterns are examined for 1967-91,
and both the levels and trends in various relative immobility
indexes are documented. As noted earlier, what is of interest is
mobility within the earnings distributions defined by the four
main subsamples and mobility within various distributions for
particular demographic groups. Table 4 reports average im
mobility measures for the 1967-91 period for the four main
subsamples. As expected, the measures are slightly higher for
the full-time, year-round samples than for the positive earn
ings samples, because, for the former, fluctuations in hours of
work are largely eliminated.
ow do mobility indexes differ across sex, age, education,
. and racial groups? Table 5 gives the 1990-91 immobil
ity indexes for both the positive earnings and full-time, yearround samples. The 1990-91 immobility measures for the posi
tive earnings sample are slightly higher for women than for
men, with differences in mobility being more pronounced at
the extremes of the earnings distributions. The table shows
that 62 percent of men remain in the bottom quintile of their
earnings distribution, compared with 70 percent of women.
Similarly, the proportion of men who stay at the top of their
distribution is 5 percentage points lower than the correspond
ing proportion of women. However, among full-time, yearround workers, the differences in mobility between the sexes
are smaller.
Table 5 also suggests that short-term immobility is typically
lower among young workers, both male and female. This find
ing is in accord with that of Donald Parsons, who compares
the National Longitudinal Survey cohorts of young men and
older men.19 Given the wider range of ages covered in the c p s ,
the current study is able to examine more closely the relation
ship between short-term mobility and age. Table 5 indicates
that short-term earnings immobility initially increases with age
and then levels off. In other words, those in their twenties
have higher mobility rates than other workers, but there is little
H
Table 4.
difference across other age groups, except within the positive
earnings sample, where workers in their fifties have signifi
cantly higher mobility rates than do workers in their forties.
This difference in regard to older workers does not exist in the
full-time, year-round sample, which implicitly controls for
variations in hours, and thus may be the result of a change in
the degree of labor force attachment as workers approach re
tirement age. The difference in mobility rates for the young is
greater for the positive earnings sample than for the full-time,
year-round sample, indicating that the high mobility rates for
the young are also partly the result of greater fluctuations in
hours. In addition, greater job mobility among the young prob
ably is an important contributor.20 The findings presented in
this article differ from the strictly positive relationship found
between 1-year earnings correlation coefficients and age in the
United Kingdom, but are broadly consistent with recent find
ings in regard to Sweden.21
Table 5 also shows a positive relationship between educa
tion and earnings stability or immobility. Within the men’s
positive earnings sample, the 1990-91 correlation coefficient
was 12 percent higher for college graduates than for high
school dropouts. Short-term earnings mobility or instability
levels were highest for those who did not complete high
school, particularly high school dropouts in the positive earn
ings sample. In both the positive earnings and full-time,
year-round samples, college graduates had significantly
lower earnings instability than those in the other education
groups. Parsons also found a positive relationship between
schooling and 1-year earnings correlation coefficients for the
National Longitudinal Survey cohort of older men, but not
for that of young men, among whom he found mobility lev
els to be highest for college graduates.22 This suggests that
the relationship between education and mobility might dif
fer across age groups.
Perhaps the most striking difference in short-term mobil
ity levels recorded in table 5 occurs between blacks and
whites. Over the 1990-91 period, the correlation coeffi
cient for black men was 16 percent lower than for their white
counterparts. These racial differences—particularly with re
gard to men—persist across both earnings samples, indi-
Average immobility measures, by earnings sample, 1967-91
Correlation
coefficient
Sample
Percent
that stay on
diagonal
Percent
that stay on
or near diagonal
Percent
that stay in
first quintile
Percent
that stay in
fifth quintile
Men:
Positive sample.....................
Full-time, year-round sample
0 .7 6
.77
57
59
88
89
65
69
71
72
Women:
Positive sample.....................
Full-time, year- round sample
.77
.78
58
59
89
89
64
67
72
74
8
Monthly Labor Review
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Federal Reserve Bank of St. Louis
September
1995
p iiiiiM H
Immobility measures by demographic group in 1990-91, using matched
Sex, age,
education,
and race
Correlation
coefficient
Percent
that stay on
diagonal
cps
positive earnings sample
Percent
that stay on
or near diagonal
Percent
that stay in
first quintile
Percent
that stay in
fifth quintile
Men
Full sample.................................................................
Age, years:
25-29 .......................................................................
30-39 .......................................................................
40-49 .......................................................................
50-59 .......................................................................
0.77
59
88
62
70
.73
.77
.75
.74
53
59
59
57
85
89
88
87
62
64
64
65
70
74
70
72
Education, years:
Fewer than 1 2 ..........................................................
1 2 ..............................................................................
13-15 .......................................................................
16 or more................................................................
.66
.70
.72
.74
53
54
57
61
83
85
87
88
58
60
69
68
69
67
69
72
Race:
W hite......................................................................
Black......................................................................
.77
.65
59
51
88
83
65
55
74
70
.78
60
89
70
75
.76
.79
.80
.76
59
61
59
59
89
88
89
88
70
71
68
66
72
74
76
72
.66
.74
.75
.75
53
57
58
58
85
87
86
88
61
68
72
67
62
71
69
68
.75
.75
61
52
89
86
68
66
73
67
Women
Full sample.................................................................
Age, years:
2 5 -2 9 .......................................................................
30-39 .......................................................................
40-49 .......................................................................
50-59 .......................................................................
Education, years:
Fewer than 1 2 ............................................................
1 2 ..............................................................................
13-15 .......................................................................
16 or more................................................................
Race:
W hite......................................................................
Black......................................................................
eating that the differences are largely due to blacks’ greater
instability in pay rates, rather than greater fluctuations in
hours worked. Evidence of a higher degree of earnings mo
bility or instability among blacks was also found by Duncan,
who used hourly earnings of males from the Panel Study of
Income Dynamics.23 The differences across races in short
term earnings mobility appear larger for men than for
women. This is consistent with the fact that the earnings
differential between blacks and whites is much smaller for
women than for men.24
Trends
This section examines the trends in three measures of earn
ings immobility over the 1967-91 period: the percentage of
individuals that stay on the diagonal in the transition ma
trix, the proportion that stay at or near the diagonal, and the
correlation coefficient. The trends in earnings mobility are
particularly interesting in light of the increase in cross-sec
tional earnings inequality observed during the 1980’s, because
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these trends affect patterns in long-run inequality. To give a
simple example, suppose an economy has just two people. In
1994, person A earns $100,000 and person B earns nothing.
Clearly, a good deal of inequality is present in this economy,
and from an equity standpoint, it may be a matter of concern.
But suppose now that in 1995, the fortunes of A and B are
reversed, so that A earns nothing and B earns $100,000. Then,
when earnings are summed up over the 2-year span, both indi
viduals have earned $100,000, so no inequality is present.
Thus, in this example, mobility is such that, even though there
is a great deal of inequality in 1 year, over a longer span the
distribution of earnings is exactly equal.
Certainly, in the U.S. economy, the degree of mobility is
not high enough so that an individual’s position in the earn
ings distribution in any year is not relevant to his or her
position as earnings are summed up over a lifetime. Even so,
there is enough mobility that the degree of inequality over
longer spans is less than that over 1 year. For example, Lee
A. Lillard estimated that inequality in a single year was 50
percent greater than over a lifetime.25
Monthly Labor Review
September
1995
9
Earnings Mobility
Chart!.
One-year correlation coefficients and immobility indexes, 1968-70, 1973-75, 1977-84, and 1986-91
Positive sample, men
Positive sample, women
1
Index 1
Index 2
Index 1
cc
Index 2
cc
-m0.9
0.9
y
0.8
^
0.8
' /
.
“
"
V - ”
•
0.7
0.7
0.6
m
MA
dfoA-M
M
«/
I ■■■
1968
I ■■■
1972
I ■■■
1976
I ■■■
1980
I ■■■
1984
I
.
1988
__1__1__1__1__1
__1
__I l l ' l l
0.4 —I— 1— 1— 1__1__1__1__1__1__1__1__1
1968
1972
1976
1980
1984
1988
Full-time, year-round sample, men
Full-time, year-round sample, women
0 .9
0.9
0.8
JKf^
%
M
Va
"
0 .8
w^\
Is
usJ \ %
^Ê
0 .7
0.7
0.6
—
0.5
0.5 -
0.4
0.6 -
-
W
t
»1
0 .6
-
f
\
\ v
/«
••* * » *
0 .5
0.4
1
1968
10
.
.
.
1
.
.
1972
.
1
.
.
1976
Monthly Labor Review
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Federal Reserve Bank of St. Louis
.
1
1980
.
.
.
1
.
1984
September
.
.
1
1988
1995
,
0 .4
— 1— 1— 1— 1___ 1___ 1___ 1___ 1___ 1___ 1___ 1___ 1___ 1___ 1___ 1___ I
1968
1972
1976
1980
1
1984
1
1
I
1
1988
1
1
1
The preceding example of a two-person economy demon
strates how, with annual inequality staying constant, move
ment in the earnings distribution can still work to reduce
inequality when earnings are summed over a longer period.
Just as mobility may help allay concerns about a degree of
inequality in one particular year, it can also help alleviate
worries about a rise in annual inequality. If annual inequal
ity rises, as it did in the 1980’s in the United States, then
this will automatically translate into higher inequality over
a longer period if there is no change in the extent to which
individuals exchange positions in the earnings distribution.
If the degree of mobility increases, however, it will reduce
the extent to which increases in annual inequality are trans
lated into increases in long-run inequality. On the other
hand, a reduction in mobility would reinforce the inequal
ity-increasing effects of rises in annual inequality.26
hat is the pattern for recent trends in earnings mobil
ity? Chart 1 graphs the trends in 1-year correlation
coefficients and two transition matrix measures for the men’s
and women’s positive earnings and full-time, year-round
samples for the period 1967-91. As mentioned earlier, four
pairs of years are missing from the time series. The missing
pairs make it difficult to distinguish much of a trend over the
early portion of the series. After this, however, short-term
immobility indexes appear to follow a stable trend. For the
men’s positive earnings sample, immobility, as measured by
the correlation coefficient, declined from 0.78 in 1977 to 0.71
in 1982 and increased moderately thereafter. This U-shaped
pattern applies as well to the men’s full-time, year-round
sample. For the women’s positive earnings and full-time,
year-round samples, 1-year correlation coefficients began to
decline sometime in the early 1970’s and rose gradually after
1978. Note, however, that the fluctuations in the correlation
coefficient graphed in chart 1 take place over a fairly limited
range. On the whole, then, the findings suggest that mobility
patterns have not been that different in the 1980’s from what
they were in the 1970’s.
What are the implications of these findings for the extent
to which increased annual inequality is being translated into
increases in long-run inequality? Clearly, additional research
is needed here, but the results presented in this article do not
suggest that mobility patterns have changed in such a way as
to offset the recent rise in earnings inequality.
More speculatively, these same results can also be used to
W
shed additional light on the causes of the recent rise in earn
ings inequality. While a detailed review of the literature on in
equality is beyond the scope of the article, one view holds that a
key factor behind the rise in earnings inequality is that the de
mand for skilled workers has increased, leading to a widening
of the earnings gap between those who are skilled and those
who are not.27 Given that such a shift in favor of the skilled
would be likely to persist over time, this has an important impli
cation for patterns of mobility: if the distance in earnings across
skill levels has widened, it becomes more difficult for individu
als to pass each other on the earnings ladder, implying that mo
bility will decline over time.
It is also possible that the increase in inequality in a given
year has been caused by increased randomness in the economy.
As Robert Moffitt and Peter Gottschalk maintain, the amount of
turbulence in the economy may have increased because of grow
ing international competition, a reduction in regulations, the
waning influence of labor unions, and a variety of other fac
tors.28 This increased influence of transitory factors would im
ply that mobility would increase, as it is more likely that, with
regard to the economic ladder, someone who has the good for
tune of benefiting from the increased turbulence will surpass
someone who has not. Because we do not see strong trends in
mobility—either a rise or a fall— the results suggest that both
the permanent factors associated with a rise in returns to skill
and the transitory factors associated with growing turbulence in
the economy may be important in the recent rise in earnings
inequality.
T h i s a r t i c l e h a s u n c o v e r e d several interesting differences
in short-term earnings mobility across demographic groups.
First, men have higher short-term earnings mobility levels than
women do. Second, workers in their twenties have high levels
of earnings mobility or instability relative to their older
counterparts. Aside from this, however, mobility levels do not
show any clear pattern with age. Third, higher education levels
generally mean higher 1-year correlations—in other words,
more stability—in short-term earnings. Fourth, black men have
more instability in their earnings than their white counterparts
have, and this racial difference in mobility levels is present, but
less pronounced, for women. Last, mobility measures followed
a general U-shaped pattern during the 1967-91 period, although
the magnitude of the shifts that occurred indicates that short
term mobility in the 1980’s was not profoundly different from
that in the 1970’s.
□
Footnotes
1For a more detailed discussion o f the importance o f data on mobility, see
A. B. Atkinson, F. Bourguignon, and C. Morrisson, “Earnings Mobility,” Eu
ropean Econom ic Review, vol. 32 (1988), pp. 619-32.
2 See Lawrence F. Katz and Kevin M. Murphy, “Changes in Relative Wages,
1963-87: Supply and Demand Factors,” Q uarterly Journal o f Econom ics,
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February 1992, pp. 35-78, for a recent study o f changes in the pattern o f pay by
age (experience), education, and sex; and Francine D. Blau and Andrea H. Beller,
“Black-White Earnings over the 1970s and 1980s: Gender Differences in
Trends,” R eview o f E conom ics an d S tatistics, May 1992, pp. 276-86, for an
examination of earnings differentials by race.
Monthly Labor Review
September
1995
11
Earnings Mobility
3 For a survey o f this literature, see Frank Levy and Richard J. Mumane,
“U.S. Earnings Levels and Earnings Inequality: A Review of Recent Trends
and Proposed Explanations,” J o u r n a l o f E c o n o m ic L ite r a tu r e , September
1992, pp. 1333-81.
4 See Lynn Karoly, “The Trend in Inequality among Families, Individuals,
and Workers in the United States: A Twenty-Five Year Perspective,” in Sheldon
Danziger and Peter Gottschalk, eds., U n even T id es: R isin g I n e q u a lity in
A m e r ic a (New York, Russell Sage Foundation, 1993), for an illuminating dis
cussion o f similar issues in studies of earnings inequality.
5 For two recent studies of mobility based on family income, see Thomas L.
Hungerford, “U.S. Income Mobility in the Seventies and Eighties,” Review o f
In c o m e a n d W ealth, December 1993, pp. 403-17; and Isabel V. Sawhill and
Mark Condon, “Is U.S. Income Inequality Really Growing?” P o lic y B ite s, The
Urban Institute, June 1992, pp. 1-4.
6 O f course, the two may be connected, as the pace of economic growth may
have implications for earnings mobility.
7 The cps is a monthly survey of approximately 60,000 households con
ducted by the Bureau o f the Census for the Bureau of Labor Statistics. The
March survey contains a special supplement that asks about income earned in
the year prior to the interview.
8 See the appendix for more information on matching cps ’s over time, in
cluding a discussion o f biases that may arise in using the matched cps ’s for
analysis.
9In lieu o f the cps , the Panel Study of Income Dynamics might have been
used; however, while the “split-offs” from the original members enable this
survey to maintain representation across all groups, the impact of attrition on
the representativeness o f the sample is an issue of concern.
10See the appendix for further information.
11 As an alternative to selecting those who are full-time, year-round workers
as a way to control for differences in hours worked, calculations were done
with samples for which the measure o f economic status was the hourly wage.
These results, which were broadly similar to the findings in this article, were
not reported for two reasons: the data necessary to calculate hourly wages from
the March cps— weeks worked in the previous year and usual hours worked
per week— are available only beginning with the 1976 cps ; and there is likely
to be substantial measurement error in calculating hourly wages by dividing
annual wage and salary income by number of weeks worked multiplied by
usual number o f hours worked per week, making the results less reliable.
O ’Neill and Solomon Polachek, “Why the Gender Gap in Wages Narrowed in
the 1980s,” Journal o f L abor E conom ics, January 1993, pp. 205-28.
16 See Bradley R. Schiller, “Relative Earnings Mobility in the U.S.,” A m eri
can Econom ic R eview , December 1977, pp. 926^11; Greg Duncan and Saul
14 See A. B. Atkinson, F. Bourguignon, and C. Morrisson, E m p ir ic a l S tu d
ie s o f E a rn in g s M o b ility (Chur, Switzerland, Harwood Publishers, 1992), for
Hoffman, “Dynamics of Wage Change,” in Martha Hill, Daniel Hill, and James
N. Morgan, eds., Five Thousand Am erican Families— Patterns o f Economic
Progress, vol. IX (Ann Arbor, mi, Institute for Social Research, 1981); and Linda
Datcher-Loury, “Racial Differences in the Stability of High Earnings among
Young Men,” Journal o f L abor Econom ics, July 1986, pp. 301-17.
17 See Jacob Mincer, Schooling, Experience an d Earnings (New York,
Columbia University Press, 1974), for an elaboration o f this view.
18 Note that no summary measures were used to assess mobility within the
overall distribution, as such measures are potentially misleading. By defini
tion, in assessing mobility within a demographic group, 20 percent of the popu
lation will be in each quintile. This is not the case when one examines the
mobility o f a demographic group within the overall earnings distribution, be
cause a group is not likely to be evenly spread across the overall distribution.
As a result, in calculating summary measures, differences across demographic
groups in the degree o f movement in and out of quintiles will get confounded
with differences across these groups in their initial distribution over the quintiles.
19 See Donald Parsons, “The Autocorrelation o f Earnings, Human Wealth
Inequality and Income Contingent Loans,” Q uarterly Journal o f Econom ics,
November 1978, pp. 551-69. The National Longitudinal Survey cohort of
young men is a nationally representative group of 5,225 men aged 14 to 24
years in 1966 who were surveyed periodically beginning that year. The cohort
of older men, with whom interviews also began in 1966, is a nationally repre
sentative group of men aged 45 to 59 years in 1966.
20 See Jacob Mincer and Boyan Jovanovic, “Labor Mobility and Wages,” in
Sherwin Rosen, ed., Studies in L abor M arkets (Chicago, University o f Chi
cago Press, 1981), for a discussion o f variation in job mobility by age.
21 See Atkinson, Bourguignon, and Morrisson, Em pirical Studies o f E arn
ings M obility; and Björn Gustaffson, “The Degree and Pattem of Income Im
mobility in Sweden,” R eview o f Income and Wealth, March 1994, pp. 67-86.
22Parsons, “Earnings, Inequality and Loans.”
23 See Greg Duncan, “An Empirical Model of Wage Growth,” in Greg
Duncan and James Morgan, eds., F ive Thousand Am erican F am ilies — P a t
terns o f E conom ic P rogress, vol. VII (Ann Arbor, mi , Institute for Social Re
search, 1979).
24 See Blau and Beller, “Black-White Earnings.”
25 See Lee A. Lillard, “Inequality: Earnings Versus Human Wealth,” A m eri
can E conom ic R eview , March 1977, pp. 42-53.
26 For a more detailed discussion o f the connections between mobility and
inequality in the context of the recent rise in earnings dispersion in the United
States, see Paul R. Krugman, The A m erican P rospect, Fall 1992, pp. 19-31.
27 For a detailed elaboration o f this view, see Chinhui Juhn, Kevin M.
Murphy, and Brooks Pierce, “Wage Inequality and the Rise in Returns to Skill,”
Journal o f P olitica l E conom y, June 1993, pp. 410-42.
a fuller discussion o f ways to measure mobility.
15 For a discussion o f this trend and potential explanations of it, see June
28Robert Moffitt and Peter Gottschalk, “Trends in the Covariance Structure
of Earnings in the U.S.: 1969-87,” mimeograph, Boston College, March 1993.
12While the 99th percentile was used as a cutoff, the bunching o f incomes,
in some cases at the top codes, caused those that were trimmed to constitute a
somewhat larger portion o f the distribution for some years. See Karoly, “In
equality among Families, Individuals, and Workers,” for a discussion of alter
native treatments o f the top code and their impact on measures of inequality.
13Results are not reported separately for the racial group defined as “other,”
because o f its small size and heterogeneity.
APPENDIX:
Construction and evaluation of matched samples from the
The data used in this article are from March-March matched files from the
Annual Demographic Files of the Current Population Survey ( cps). At the time
o f the analysis, the cps was available for the period 1968-92, containing earn
ings data for the year prior to the interview. While that implies the existence of
24 adjacent-year pairs o f records (1968-69 through 1991-92), changes in
household identifiers across adjacent years make it impossible to perform
matches for 1 9 7 1 -7 2 ,1 9 7 2 -7 3 ,1 9 7 6 -7 7 , and 1985-86. Thus, we were able
to construct matched files for 20 pairs o f years between 1968 and 1992.
Under the sample design of the cps, half of any March sample can be matched
12
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September
1995
cps
with the March sample o f an adjacent year. A household will be in the sample
for 4 months, out for 8 months, and then back in for an additional 4. Thus,
households that are in their first through fourth months in the sample in March
of year t will be in their fifth through eighth months in the sample in year t + 1.
In practice, it is not possible to match fully half of the sample, given that indi
viduals leave it for various reasons. The match rates used in this article result
from a fairly conservative algorithm and tend to fall in the range of 60 percent
to 70 percent of individuals who are eligible to be matched. This attrition rate
raises the concern as to whether matched samples can be considered rep-
resentative. Franco Peracchi and Finis Welch recently subjected matched
March samples to a rigorous testing and concluded that, while the matched
and unmatched populations are different in important dimensions, “no
major biases appear in the estim ates o f transitions between labor force
states after controlling for sex, age and labor force status at the time o f
the first survey.”1W hile the research focus o f the current article is differ
ent from theirs, Peracchi and W elch’s results provide som e support for
using matched cps data in analyzing labor force dynamics. One caveat they
mention is that attrition rates are highest among the very young. Similar
conclusions were reached in an earlier analysis by Francis W. Horvath.2
Accordingly, to m inim ize attrition problems in the present research, very
young workers were omitted from the samples and analyses were performed
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separately by age group. One of the sensitivity tests that was carried out involved
the calculation of inequality statistics for various samples from the matched data.
The results indicated that both the levels and trends obtained are comparable to
those calculated from the full March CPS.
Footnotes to the appendix
1 See Franco Peracchi and Finis Welch, "How Representative Are Matched
Cross-Sections: Evidence from the Current Population Survey," unpublished
manuscript, October 1992.
2 See Francis W. Horvath, "Tracking Individual Earnings Mobility with the
Current Population Survey," M o n th ly L a b o r R e v ie w , May 1980, pp. 43-46.
Where are you publishing your research?
The Monthly Labor Review will consider for publication studies of the labor force,
labor-m anagem ent 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.
Monthly Labor Review
September
1995
13
Labor Force Attachment
M
Effects of intermittent labor force
attachment on women’s earnings
Women who leave the labor market fo r family reasons
often return to wages lower than those o f women who did not;
they lose seniority; are less likely to receive on-the-job
training, their job skills may depreciate,
and employers may believe they will again take a leave
Joyce P. Jacobsen
and
Laurence M. Levin
Joyce P. Jacobsen is a
professor of economics
at Wesleyan University;
Laurence M. Levin is an
associate at
Cornerstone Research,
Menlo Park, CA.
14
omen who interrupt their careers and
leave the labor market for family re
sponsibilities often return to find that
their wages lag behind those of women at com
parable stages in their careers who did not leave
the labor force.
Many reasons account for this lag. First,
women who leave the labor force and later re
enter do not build up seniority, which, by itself,
often leads to higher wages. Second, women who
return to the labor force are less likely to receive
on-the-job training to increase their productiv
ity and thereby raise their pay. Third, when
women are not in the work force, their job skills
may depreciate. Finally, employers may view
gaps in work history as a signal that women who
leave may do so again. Some employers would
therefore hire them for less important, lowerpaying jobs to limit the impact of a future deci
sion to leave.
But calculating the cost of intermittent labor
force attachment is difficult. Typically, these
costs are measured in terms of earnings paths;
women who leave the labor force have lower
earnings paths than those of women who
remain.
This article calculates the cost of taking a
break from work in terms of the wage differ
ence between women who work continuously
and women who take one or more leaves. We
attempt to control for observable and unob
servable heterogeneity to uncover temporary
and lasting effects a gap in labor force attach
ment can have on wages.
W
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September 1995
Previous research
Most researchers would agree that earnings will
be less for workers who take a break from work
than for those who work continuously. But re
searchers are generally less likely to agree on
the magnitude of this effect. Those who do not
leave the work force tend to be younger and bet
ter educated than those who do. Therefore, us
ing the group that has worked continuously as
the standard for what would have been earned
had a worker not taken a break would over-esti
mate foregone earnings.
In addition, cross-sectional estimates may be
biased by cohort effects that obscure the wage
changes a woman may experience when she re
enters the labor market. Nevertheless, studies that
run earnings regressions to correct for observable
differences and that include some measurement of
effects of gaps in labor force participation reveal
that gaps affect earnings.1 In qualifying these re
sults, researchers have focused on different aspects
of the effects of intermittency. One hypothesis is
that earnings will rebound soon after women re
enter the work force.2 However, L.S. Stratton sug
gests that the rebound effect after re-entry doesn’t
occur.3 She hypothesizes that women returning to
the work force who find their wages lower than
they had expected are quite likely to leave again.
Thus, Stratton concludes, over time only the rela
tively high-earning women who have had a break
in labor force participation will be left in the work
force.
This article tests for the rebound effect by re-
striding the sample of women with labor force breaks to
those women who display continuous labor force attachment
for an extended period after a break. By limiting the sample
to this subgroup of women, one source of unobservable het
erogeneity is eliminated. Furthermore, by holding the
sample constant and examining wages at several points in
time, we can closely study the effects of increasing time fol
lowing a work gap.
Our results differ from those of J. Mincer and H. Ofek,
and Stratton. We find that when women re-enter the labor
market, their earnings are much lower than those of a com
parable group of women who did not leave the labor market.
Over time, that difference diminishes (due to the rebound
effect), but never disappears, even after as long as 20 years.
The data
The data used in this study are from the 1984 panel of the
Survey of Income and Program Participation.« Each indi
vidual in the data set was placed in 1 of 4 rotation groups
that were interviewed in successive months, and was inter
viewed eight times at 4-month intervals. Participants were
asked in each interview about their labor force participation
in the previous 4 months.
This technique produced data for 32 consecutive months
for each individual, with a sample period covering June 1983
to April 1986. In addition, the survey contains detailed work
histories of individuals before they entered the sample. These
work histories are used to identify gaps that occurred before
the sample period began.
How the sample was selected. Only women aged 30 to 64
at the start of the sample are included. The lower age limit
allows women sufficient time to have had at least one work
interruption. Second, only women who work relatively con
tinuously during the 32 months of the sample are included.
To be included in the sample, a woman must report earnings
in the 1st, 6th, 12th, 18th, 24th, and 32nd months of the
sample.6 Thus, women are included only if their gaps in the
sample period were shorter than 6 months. In this study, we
are not interested in modeling earnings effects from short
leaves, such as maternity leaves; we are trying to include the
majority of women, such as teachers, who have seasonally
intermittent work schedules.
To be included among the sample of women with labor
force breaks, a woman must have taken at least one break
from work of 6 months or longer between the year she
received her last educational degree6 and the beginning
of the survey.7 This includes women who worked before
taking a break, and women who had an initial gap be
tween the year of their last degree and the year in which
they started working.»
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The unadjusted geometric mean wage ratio of those who
left the work force and those who did not is 1.33 at the start
of the sample and falls to 1.30 after 32 months.^ (See table
1.) Women who did not leave the work force are signifi
cantly younger and have more education on average than
PaU&Us U
S a m p le m e a n s for w o m e n w h o r e m a in e d in th e
la b o r fo rc e (n o g a p s ) a n d w o m e n w h o left th e
la b o r fo rc e (1 or m o r e g a p s ) in th e first m o n th o f
th e s a m p le
Item
Women who remained Women who left
in the work force
the work force
(no gaps)
(1 or more gaps)
Number of people..................
Wage (T = 1).........................
(T = 1 8 )......................
(T=32).......................
Log wage (T=1)...................
(T=18)..................
(T=32)..................
696
8.83
9.72
9.76
2.07
2.16
2.17
. 1,730
6.61
7.23
7.49
1.78
1.87
1.91
Years of education.................
Percent without high..........
school diploma..................
Percent with high
school diploma..................
Percent with some college..
Percent with college
degree..............................
Percent with graduate
work .................................
19
6
Age distribution.....................
Percent part-time................
Total years worked..............
39
12
17
45
24
17
38
21
10
2
17
3
Occupational group:
Percent professional/
executive...........................
Percent service
occupations.......................
Percent craft occupations...
Percent pink collar/blue
collar .................................
Residence in South................
Residence outside
Metropolitan
Statistical Areas..................
14
12
6
21
33
27
47
19
15
7
50
59
20
16
24
25
Race/ethnicity:
White (non-Hispanic)...........
Black (non-Hispanic)...........
Hispanic...............................
Other.....................................
81
13
3
3
82
11
3
4
Marital status:
Married..................................
Widowed..............................
Divorced...............................
Never married......................
58
3
21
18
70
5
21
4
Number of children ever born:
N o n e.....................................
1 ............................................
2 ............................................
3 or m o re.............................
39
18
24
19
9
14
33
44
-
6
5
14
24
33
18
Years since last gap (at T=1):
0 to 1 year............................
2 years.................................
3 to 5 years..........................
6 to 10 years........................
11 to 20 years......................
More than 20 years.............
NOTE:
-
-
Dash indicates data are not applicable.
Monthly Labor Review
September 1995
15
Labor Force Attachment
those who did leave. Total work experience is the same for
the two groups, which reflects the higher age and lower edu
cational attainment of the women who left the work force.
These women are much more likely to be working part-time
and are more heavily represented in the service occupations
and the lesser-skilled occupations, both blue-collar and
“pink-collar” (such as administrative support occupations,
medical technicians, and machine operators).
omen who leave the work force are more likely to be
married and to have children than are their counter
parts who remain in the work force. For the women who
leave work, the average length of time since their last gap
was 13 years.10 This last gap lasted an average of 7.5 years,
although the median, at 4.5 years, was shorter. Of the women
who answered the question, “What was the reason for the
last gap?,” 85 percent responded that this leave from the
labor force was for family reasons. Other possible reasons
included poor health and inability to find a job; leaving work
to attend school is not counted as a gap.
The unadjusted data show an average annual rate of wage
growth of 3.9 percent for women who don’t leave the labor
force and 4.7 percent for women who have left the labor
force. However, over the last 14 months of the sample, the
annual rate of wage growth is 0.6 percent for women who
haven’t left work, compared with 3.1 percent for those who
have.
The observed differences between the two groups in
education and occupational distribution, and in marital status
and number of children, are significant, and lead to our use
of multiple regression analysis below. We do not attempt to
address the issue of whether women plan their human capital
investments in anticipation of future gaps, nor do we attempt
to differentiate between people who did or did not intend to
leave the labor force. However, anticipation of leaving the
labor force can lead to lower earnings over a woman’s
worklife if she invests in less human capital, or in human
capital that yields lower returns, but depreciates at a slower
rate during periods when a woman has left the work force.11
These investment effects on earnings are not measured here.
One argument that could be made is that women who leave
the labor force earn less money to begin with than do their
counterparts who remain at work. According to this argu
ment, their lower wage upon reentry does not indicate a sig
nificant loss relative to their earning power before exiting
employment. To address that question, we looked at the sub
set of this group (25 percent of women who leave the labor
force) who reported the wage they were receiving at the time
they began their last separation from work.
This subsample is slightly younger than women in ge
neral who have left work (43 instead of 45 on average); the
length of time they have been out of work is skewed toward
W
16
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September 1995
shorter lengths (54 percent have been working 5 or fewer
years since ending their last period away from work; 13 and
their wage in the first month of the sample is lower ($5.93
instead of $6.61).13 We expressed their previous wage in
1984 dollars to correct for the rate of price change, as mea
sured by the Consumer Price Index.
Because the c p i generally increased by less than the rate of
growth of nominal wages, we are biasing against a finding
that would support our work, which is that wages depreciate
significantly during a gap. Yet we find that the wage earned
by sample members before beginning their last gap had a
mean of $7.76, which is more than 30 percent higher than
their wage in the first month of the s i p p sample. This implies
that because the majority of women who left the work force
had been working for several years when they entered the
survey, their wage upon reentry to employment was even
lower.
This is a substantially different result than was found in
the work of Corcoran and Stratton, who also use U.S. data,
but from the Panel Study of Income Dynamics and the Na
tional Longitudinal Survey of Young Women. Their studies
find little depreciation when comparing the wage before leav
ing work with the wage earned upon returning to work. Our
data are telling a different story about wage changes due to
gaps in work.
Empirical results
The next step in our analysis was to estimate regressions
whose dependent variable was the natural logarithm of the
hourly wage. A regression equation will show the direct ef
fects on wages of gaps occurring at different times in the
past, and will allow for calculation of wage ratios that con
trol for differences in age, education, work experience, and
other factors between those who have left the work force and
those who remained at work. (See table 2.) The regression
equation is estimated at three different points in the sample:
the 1st, 18th, and 32nd month of the sample period.14 The
independent variables are divided into two types. The first
includes variables that control for individual characteristics
including age, geographic location, occupation class, and
human capital.
The second type of variables is a set of dummy variables
for number of years since a worker ended her last absence
from the labor force, measured from the beginning of the
survey; for any observation, the values of these dummy vari
ables are the same in all three equations. For example, a
woman who concluded a work gap in the year before the
survey began will be assigned the dummy variable for a 1year absence for all 3 years; as a result, for her the coeffi
cient on the dummy will stand for the effect of one year since
the absence ended in the first equation, two years since the
Table 2.
Regressions on log wage, at three points during
the sample period
Item
Time since gap (at T=1):
0 to 1 year........................................
2 years.............................................
3 to 5 years......................................
6 to 10 years....................................
11 to 20 years.................................
More than 20 years........................
Total years worked..........................
Hours and weeks less than
35 (1=yes).......................................
South (1=yes)....................................
Rural (1=yes).....................................
A ge....................................................
A ge2 1,000 .................................
Education level (no high school
diploma is omitted class):
High school diploma.......................
Some college..................................
Bachelor’s degree...........................
Graduate work................................
Occupation (pink collar/blue
collar omitted class):....................
Professional...................................
Service .................................
C raft..........................................
Intercept......................................
Log wage (dependent variable
m ean).......................................
Adjusted R2 ...................................
n o te
:
T=1
T=18
T=32
-0.33
(7.51)
-.2 7
(5.58)
-.2 0
(6.28)
-.1 2
(4.73)
-.1 0
(4.08)
-.0 7
(2.11)
.003
(2.67)
-0.29
(6.85)
-.2 7
(5.99)
-.1 4
(4.76)
-.10
(4.23)
-.0 7
(3.17)
-.08
(2.77)
.004
(3.64)
-0.20
(4.61)
-.2 4
(5.13)
-.1 6
(5.30)
-.0 7
(2.64)
-.06
(2.61)
-.05
(1-76)
.003
(2.89)
-.1 3
(6.28)
-.0 7
(2.90)
-.1 5
(7.91)
.02
(2.06)
-.24
(2.24)
-.15
(7.67)
-.0 7
(3.49)
-.1 5
(8.15)
.01
(1.24)
-.16
(1.60)
-.15
(7.17)
-.0 8
(3.45)
-.1 6
(8.59)
.01
(1.43)
-.18
(1.74)
.13
(5.11)
.27
(9.28)
.32
(8.62)
.41
(10.35)
.11
(4.59)
.25
(8.81)
.32
(8.95)
.44
(11.70)
.10
(4.20)
.25
(8.70)
.30
(8.29)
.43
(11.19)
.20
(8.54)
-.2 5
(10.16)
.14
(2.85)
1.39
(6.69)
.21
(9.57)
-.2 9
(12.37)
.10
(2.25)
1.67
(7.91)
.17
(7.79)
-.28
(11.25)
.06
(1.21)
1.63
(7.21)
1.86
.35
1.96
.40
1.98
.36
Coefficients significant at the .05 level, t-statistics in parenthesis.
absence in the second equation and three years since the ab
sence in the third. Measuring the dummy variables this way
allows us to examine if the wages of the same group of
women change as the amount of time lengthens over the
duration of the survey since the end of their last period out of
the labor force.
A lasting negative effect and a gradual rebound effect re
sulted from the period out of the labor force. (See table 2). The
coefficients on the dummy variables that control for the num
ber of years since the last period out of the work force clearly
show that the large initial negative effect of the work gap de
creases as the gap recedes into the past. In addition, examining
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the 3-year pattern of the dummy coefficients provides strong
evidence that the decline in the negative effect of a gap is not
due solely to women with low wages leaving the labor market.
For every period out of the labor force, the value of the
dummy coefficient is largest in the first period and smallest
in the last, implying that for any particular length of time
out of the labor force, 2-1/2 years of continuous labor force
attachment will, on average, diminish the difference in wages
between those who have left the work force and those who
remained. For example, in the initial period, women whose
gaps ended less than 1 year ago had wages that were 33
percent lower than those of women who did not leave the
labor force. By the third year (when they would have re
turned to the work force more than 3 years ago) these
women’s wages were only 20 percent lower than those of
women who remained in the labor force. This coefficient is
the same as the coefficient on the dummy variable that
women whose last gap was between 3 years and 5 years ago
received in the regression for the first period.
The results reported above held, regardless of changes to
the equations described below.15 Initially, different equations
were used for those who left and those who remained in the
labor force. The two groups were combined and an F-test 16
of whether the two groups could be pooled was conducted;
the test did not reject the hypothesis that the two groups could
be pooled. Therefore, only the pooled results are shown.
Alternative specifications included three possibilities:
• including a variable for the total length of the last period
out of work, or including a set of variables for length of
this period interacted with the dummies modeling time
since the end of this period;
• marital status, either as a dummy variable for whether or
not the woman was currently married, or as a dummy
variable for whether or not the woman had ever been mar
ried;
• either a dummy variable noting whether the woman had
ever had children, or a continuous variable for the num
ber of children ever born.
These alternative specifications did not substantively
change the results, although the above variables had a very
small (but statistically significant) negative effect. However,
the dummy variable that indicated currently married was sta
tistically insignificant.
Another alternative specification included a set of vari
ables using a dummy indicating whether the length of time
out of the labor force was more than 4 years (the median gap
length), which was interacted with the dummies modeling
elapsed time since the gap. This set of additional variables
did not pass an F-test for significance of their inclusion. A
variable indicating whether the person had numerous peri
ods out of the labor force was not significant; neither was a
Monthly Labor Review
September 1995
17
Labor Force Attachment
quadratic term in experience, nor a variable indicating
whether the employee generally worked full-time or parttime throughout her worklife.17
Including local labor market features, such as monthly
unemployment rates by State, also was not significant.18 Fi
nally, including a dummy signifying nonwhite or Hispanic
status was not significant, and a pooling test for whites and
nonwhites did not reject the hypothesis that the two groups
could be pooled.
lthough there is strong evidence for a partial rebound
effect, the wages of women who have taken a leave from
the labor market never catch up to the wages of women who
never left. Even women whose labor force gap occurred more
than 20 years ago still earn between 5 percent and 7 percent
less than women who never left the labor force and have com
parable levels of experience; in the last year, however, this dif
ference is significant only at the 10-percent significance level.
One possible interpretation is that even after many years,
employers view work gaps as a signal that the individual is not
as dedicated a worker as a woman who did not leave the work
force. This view may be reflected in reduced promotion possi
bilities, different job assignments, and other actions by em
ployers that reduce wages.
To illustrate the cost of taking an employment gap for a
particular case, assume a woman with the following character
istics: graduates college at age 21, immediately begins full
time work (40 hours a week, 50 weeks a year) in a pink-collar
occupation, lives in a city outside the South. She leaves work
when she is 25 years old for 7 years and re-enters full-time
work in 1984 at age 32. We assume a real interest rate equal to
the rate of real wage growth and use the growth rates calcu
lated from the regression for time t= l. In this case, the present
(1984) value of the difference between her earnings for the 20
years after she re-enters and what they would have been had
she remained constantly employed is $52,000. Part of this is
caused by her fewer years of experience; part is due to her
decision to leave the labor force. This amount is equal to 15
percent of her prospective earnings had she worked constantly,
or approximately 3 years of wages—a considerable difference.
Thus, the cost of taking a 7-year gap is 10 years of earnings.
Unadjusted geometric mean wage ratios and adjusted
geometric mean wage ratios that are calculated using the
regressions reported are listed in the following tabulation.
The adjusted geometric mean wage that is calculated using
the regressions illustrates how much of a wage differential
remains between the groups of women who did not leave the
work force and those who did, even after controlling for
A
differences in mean values between the two groups:
Unadjusted
t = l ..........................................
t= 1 8 ........................................
t= 3 2 ........................................
1.33
1.34
1.30
Adjusted
1.14
1.12
1.10
The first column displays the unadjusted ratios of wages of
women who did not leave the work force to those who did at
the three points in time of the sample. The second column holds
differences in mean values for age, education, total years expe
rience, and so on, constant for the two groups. It is calculated
by taking the antilog of the negative of the summation of each
gap dummy coefficient multiplied by the proportion of the
women who left work experiencing the length of the gap in
labor force participation. This has the effect of reducing the
wage differential at each point in time, but does not eradicate
it, indicating that a work gap is important in explaining differ
ences in earnings between the two groups.
Additionally, the pattern of a rebound effect is demon
strated more clearly by holding constant other factors affect
ing the wage. After 32 months, the adjusted ratio has dropped
from 1.14 to 1.10, indicating that women who remained at
work still receive a wage 10 percent higher than their coun
terparts who left the labor force.
I n s u m , optimists and pessimists can take some solace from our
results. On the optimistic side, wages that drop because of a
break from the work force rise over time. On the pessimistic
side, however, the negative effects of a break in earnings are
quite persistent; they remain discernible even 20 years after the
last break has ended.
In addition, the effect of a gap on a woman’s lifetime earn
ings is significantly larger than just her foregone wages during
the time away from work. This last finding has significant im
plications for the way in which compensation between hus
band and wife is calculated in divorce proceedings.
One obvious extension of this work is to discuss the malefemale wage ratio and the contribution that gaps in work make
toward explaining the gender pay gap. Another extension is to
develop a model that simultaneously predicts who will take a
leave from work with what womens wages will be in various
life situations. This will allow our analysis to be extended to all
women rather than just the specific subset we analyze in this
article. The narrower focus of this article, however, has allowed
for discussion of the rebound effect, and has provided a clearer
idea of how sustained gaps in employment can influence female
earnings.
□
Footnotes
ACKNOWLEDGMENT :
The data used in this paper were made available by the
Inter-university Consortium for Political and Social Research. The data for
Survey o f Income and Program Participation, 1984 panel, were collected by
18
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September 1995
the U.S. Bureau of the Census. Neither the collectors of the original data nor
the Consortium bears any responsibility for the analyses or interpretations pre
sented here.
Financial support from the Rhodes College Department of Economics and
Business and Santa Clara University, and comments on an earlier version of
this paper from Jean Kimmel, John Pencavel, Leslie Stratton, and participants
o f sessions at the 1991 Southern Economic Association, 1992 American Eco
nomic Association, and 1992 International Economics Association conferences
are all gratefully acknowledged.
1 M.B. Stewart and C.A. Greenhalgh, “Work History Patterns and the
Occupational Attainment of Women,” E c o n o m ic J o u rn a l, September 1984,
pp. 493-519, using British data; M.E. Corcoran, “Work Experience, Labor
Force Withdrawals, and Women’s Wages: Empirical Results Using the 1976
Panel o f Income Dynamics” in C.B. Lloyd, E.S. Andrews, and C.L. Gilroy,
eds., W om en in th e L a b o r M a r k e t (New York, Columbia University Press),
1977, using U.S. data.
2 Jacob Mincer and Haim Ofek, “Interrupted Work Careers: Depreciation
and Restoration o f Human Capital,” J o u r n a l o f H u m an R e s o u r c e s , Winter
1982, pp. 3-24.
3 "The Effect Interruptions in Work Experience Have on Wages," S o u th ern
E c o n o m ic J o u rn a l, April 1995, pp. 955-70. Stratton acknowledges that the
direction o f causality can go both ways— from low wages to labor force expe
rience or from planned experience to low wages.
4 Later panels o f the sipp do not contain equally detailed data concerningwork gaps. The extracted data and the programs used to create and analyze the
data set are available upon request from the researchers.
5 This corresponds to data from the 1st, 2nd, 3rd, 5 th, 6th, and 8th waves of
the panel.
6 Seven percent o f the women counted as those who did not leave the work
force reported a gap, but continued their formal education during that period.
7 Gaps shorter than 6 months are not coded in the data, so the minimum gap
length was determined by data availability.
8 O f the women who are counted as those who left the labor force, 15.8
percent did not report a gap since beginning work; for these people, the exist
ence and timing o f a gap since completing their formal education was calcu
lated in one or both o f two ways: by determining if subtracting the total number
o f years they reported working continuously left time unaccounted for between
then and when they finished school; or by determining if the year that they first
reported having a job was more than 1 year after they reported finishing school.
Exclusion of these women does not substantially change the numbers reported
in tables 1 and 2.
9 The reported normal hourly wage rate is used when available; when not
reported, a measure of average hourly earnings was constructed to proxy for
the wage rate. This measure was constructed as monthly earnings divided by
monthly hours worked. This measure was used for 42 percent of the sample in
the 1st month, 45 percent in the 18th month, and 43 percent in the 32nd month.
10 Only 7 percent of the women who left work reported more than one gap of
6 months or longer.
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11 Unlike Stratton, our focus in this article is not on a woman’s earnings
upon reentry relative to what she made before leaving the work force, but rather
on her earnings relative to what she would be making had she been working
continuously. We are unable to address the first issue because we do not have
observations that would apply to more than a small percentage of the women of
each woman’s wage before she left the work force. However, these are different
questions, and the rebound effect can be measured in either case (although rela
tive to a different base) over the period of work following work force reentry.
12 This skewing toward shorter lengths is caused by the availability o f the
data on previous wage. Women were not asked in the sipp what their wage was
before their last gap; they were asked what their wage was on their previous
job. Women who have been working for longer periods since their last period
out of the work force have had more opportunity to switch jobs. As the sipp also
contained data on years in which the previous job had ended and how much
time had elapsed before the current job began, we could determine which
reportings o f previous wage corresponded to a wage earned before a period out
of the work force.
13 O f these women reporting their previous wage, 58 percent reported their
hourly wage, 17 percent their weekly wage, 15 percent their monthly wage,
and 10 percent their annual wage. All wages were translated into hourly wage
rates using the additional reported variable of usual hours worked per week on
previous jobs; for monthly and yearly wages, the hours variable was multiplied
by 4.3 or 50 to estimate total monthly and total yearly hours.
14 This corresponds to data from the first, fifth, and eighth waves o f the sipp
panel.
15 All of these alternative regressions are available from the authors upon
request. The sample size is reduced to 1,823 women, 523 o f whom worked
continuously, upon inclusion of information about the presence of children.
16 This test, often referred to as the Chow test, consists of estimating the
regression equation for the two groups separately and then together, and calcu
lating the statistic:
F = (R R S S - U R S S )/( k + 11
URSSKn + n
1
- 2 k -2)
2
where R R S S = the sum of the residual sum o f squares from the separate equa
tions, U R S S = the residual sum of squares from the pooled equation, k = the
number o f independent variables n, and n2 = number of observations the two
groups respectively. Then the statistic has an F distribution with degrees of
freedom (k + 1), {n { + n2 - 2 k - 2). If it is not sufficiently greater than zero, then
the hypothesis that the equation structure and the two groups are not different
cannot be rejected.
17 Seventeen percent o f women who left work and 9 percent o f women who
worked continuously reported they generally worked part-time.
18 Thanks to Jean Kimmel for providing these data.
Monthly Labor Review
September 1995
19
Security Brokers and Dealers
Employment trends in the security
brokers and dealers industry
Employment o f wage and salary workers
in this industry grew by 28 percent
between 1984 and 1993; professional jobs
almost doubled , while weak job growth
fo r clerical workers reflected productivity
gains from technological advances
Brett Illyse Graff
A
Brett lllyse Graff is
an economist in
the Office of Em
ployment and Un
employment Sta
tistics, Bureau of
Labor Statistics.
20
s global markets have expanded and com
puterized trading has increased, tasks per
formed by workers in many occupations
in the security brokers and dealers industry have
been transformed. The most recent data collected
on occupational staffing patterns in the industry
reflect the component firms’ adaptation to conse
quences of the 1987 market crash and to decades
of electronic advances. The industry has re
sponded to these changes by increasing employ
ment in highly technical professional occupations
such as computer scientists and statistical finan
cial analysts, and by streamlining managerial and
internal analysis jobs. The increase in the profes
sional share of the industry’s employment has
largely offset a decrease in the managerial share.
This article examines the changes in occupational
employment within the security brokers and deal
ers industry through some of the steepest bull and
bear markets of the post-World War II period.
Industry profile
The security brokers and dealers industry (sic
621)1 includes bond dealers and brokers, mutual
fund agents, security traders, securities underwrit
ers, oil and gas lease brokers, and tax certificate
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September
1995
dealers. In May 1993, it employed 349,880 work
ers. (See table 1.) The industry is a component of
securities and commodities brokers, dealers, ex
changes, and services (sic 62).
Brokers in this industry act as agents in secu
rity transactions for individual and institutional
clients. Dealers buy and sell securities for their
firm’s own account and risk.2 Investment bank
ers, also included in this industry, are primarily
engaged in the initial public offering of securi
ties. They underwrite and distribute shares, while
generally continuing to act as market makers in
those issues.
Broker-dealers are required to register with the
Securities and Exchange Commission (SE C ), a
Federal agency that governs several self-regulated
organizations (S R O ’s ) . They also must obtain
membership in the National Association of Secu
rities Dealers (N A S D ). A broker-dealer distribut
ing new issues underwritten by NASD members,
or distributing shares of investment companies
sponsored by N A SD members,3 must become a
member of the NASD.
Firms trading on the Nasdaq market (the overthe-counter market) as either strictly order-entry
firms (trading as brokers or dealers) or market
makers (dealers that hold an inventory of Nasdaq
listed securities) must meet NASD requirements. Nasdaq is an
electronic trading network. The Nasdaq Workstation n pro
vides a centralized quotation service, as well as automated ex
ecutions, trade reporting, and trade negotiation.4 Traders us
ing the Nasdaq system can link to the major exchanges through
the Computer Assisted Execution System Intermarket Trading
System ( c a e s / i t s ).
If a firm is brokering or dealing stocks listed on an exchange,
it is often a member of that exchange. To become a market
maker in an exchange listed security, a firm must apply to the
exchange. Unlike the case for Nasdaq, each security trading on
an exchange can only have one market maker. By using a cor
respondent firm to clear and execute its trades, a firm can trade
on an exchange without being a member.
Chart 1 shows the trading volume within the major world
securities markets. It displays the significance of both the
New York Stock Exchange ( n y s e ) and Nasdaq. The high
number of members and the consequential trading volume
on the n y s e cause the resulting data from this organization
to be used as a proxy for the operations of the entire industry.
Industry employment
Inflation during the late 1970’s caused many companies to
begin to trade at undervalued prices, and by the early 1980’s,
lower interest rates helped to make purchasing securities lu
crative. In August 1982, the market began a 5-year ascent.
Table 1.
Industry employment for March of that year totaled 219,620.5
By 1984, brokerage firm profits were down from the previ
ous year, but stock prices continued to rise. The Quarterly
Dow Jones Industrial Average ( d j i a ) had increased by 26.3
percent,6 and total industry employment in May of that year
had risen by 24 percent (to 273,330) from the 1982 level.
By 1987, stock prices in relation to their underlying value,
as measured by earnings potential, had become inflated.7
The Quarterly d j i a was up 113.5 percent from its 1984 level.
As of May of 1987, industry employment had increased by
25.6 percent (273,330 to 343,170) from the 1984 level. By
October, several factors, including a weakening U.S. dollar,
expectations of rising inflation and interest rates, and wid
ening yield spreads between stocks and bonds, sent investors
on a selling spree. The market crashed and the Quarterly
d j ia fell 657.45 points between the third and fourth quarters
(September 30 to December 31). Pretax profits of firms in
the industry were down $4,379 billion8 from the previous
year.9 Even so, employment rose to 358,475 in December,10
but decreased by 0.9 percent by the end of the first quarter of
1988.“ By the end of that year, total trading volume was
down on the American Stock Exchange (AM EX), NYSE, and
Nasdaq.
The crash resulted in extreme cost cutting in the industry.
In 1989, bonuses were down, on average, approximately 20
percent. Some firms sought to conserve cash by giving stock
to their employees.12 By May of 1990, employment had
Occupational employment within security brokers and dealers, selected years, 1984-93
1984
Occupation
Employ
ment
1987
Percent
distri
bution
Employ
ment
1993
1990
Percent
distri
bution
Employ
ment
Percent
distri
bution
Employ
ment
Percent
distri
bution
Total industry...............................................................
273,330
100.00
343,170
100.00
325,230
100.00
349,880
100.0
Managerial occupations....................................................
Financial managers.........................................................
General managers and top executives
(brokerage managers)................................................
21,450
3,890
7.81
1.42
33,170
8,420
9.63
2.45
31,050
10,480
9.51
3.22
25,360
9,290
7.25
2.66
8,360
3.05
15,470
4.50
12,080
3.71
11,020
3.15
Professional occupations................................................
Accountants and auditors..............................................
All other financial specialists..........................................
Systems analysts............................................................
Computer programmers.................................................
Operations and systems analysts, except computer...
Financial analysts, statistical..........................................
Economists, including market researchers...................
27,720
4,230
1,720
2,180
3,440
260
3,700
1,940
10.01
1.54
.62
.79
1.25
.09
1.35
.70
44,490
4,960
6,120
2,930
5,680
1,490
5,300
1,840
12.81
1.44
1.78
.85
1.65
.43
1.54
.53
47,290
5,570
13,560
4,090
4,900
1,110
5,330
1,570
14.50
1.71
4.16
1.25
1.50
.34
1.63
.48
54,380
4,950
17,000
3,080
5,040
350
6,380
2,040
15.50
1.41
4.86
.88
1.44
.10
1.82
.58
Sales and related occupations.........................................
First-line supervisors......................................................
Sales agents—securities, commodities,
and financial services..................................................
105,530
5,500
38.60
2.01
119,470
5,020
34.78
1.46
123,430
7,680
37.90
2.36
138,010
4,410
39.40
1.26
89,100
32.60
103,210
30.07
103,770
31.90
122,500
35.01
Clerical and administrative support workers...................
First-line supervisors.......................................................
Brokerage clerks............................................................
Secretaries......................................................................
Data-entry keyers............................................................
116,930
4,800
37,660
26,700
3,440
42.60
1.75
13.77
9.76
1.25
142,200
11,640
40,410
31,660
4,070
41.26
3.39
11.77
9.22
1.18
119,930
9,210
35,390
29,070
2,810
36.70
2.83
10.88
8.93
.86
129,140
10,700
44,230
26,040
2,030
36.90
3.06
12.64
7.44
.58
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Monthly Labor Review
September 1995
21
Security Brokers and Dealers
Chart 1,
Dollar volume of equity trading in major world markets, 1994
Stock exchange
$500
$1,000
$1,500
Value (in billions of U.S. dollars)
$2,000
$2,500
b y ^ r m ^ io n nal Association of Securltles Dealers, Inc., 1995 N a sd a q Fact Book & C om p a n y Directory (Washington, naso, 1995).
$3,000
Reprinted
Chart 2. Average weekly wages in security brokers and dealers and in total private industry, selected years,
---------- 1984-1993
Wages
Wages
$2,000 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------$2,000
□ Security brokers and dealers
$1,800
■ Total private industry
-
$1,600
$1,400
$ 1,200
$
1,000
-
$800
$600
$400
$200
$0
1984
22
Monthly Labor Review
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Federal Reserve Bank of St. Louis
1987
September
1995
1990
1993
decreased by 5.2 percent from the 1987 level, and totaled
325,230. That year, firms in the industry posted a loss of
$162 million before taxes. Between the second and third
quarters (June 29 to September 28) of 1990, the Quarterly
d j ia plummeted again, dropping 428.21 points. It moved up
181.18 points the following quarter and a total of 535.17
points over the following year.
In 1991, the market began a dramatic recovery, which led
to spectacular performances in almost every product category.
Lower short-term interest rates caused investors to favor
stocks and bonds over low-yielding bank instruments.13 The
pretax profits of firms surpassed those of 1986. Industry
employment, however, continued to fall until February of
1992. Later that year, the average daily trading volume on
the Nasdaq doubled, while n y s e trading volume increased
69 percent.14 Employment began to inch back up. Trading
volume alone was enough to move up the market, but the cost
cutting resulting from the 1987 crash and the privatization
of state-owned enterprises worldwide also contributed to the
prosperity. Mutual fund sales set successive records in 1991,
1992, and 1993.15 Pretax profits for industry establishments
in 1993 reached a record $8,600 billion.16 By May of that
year, the industry’s employment had increased 7.6 percent
from 1990, totaling 349,880.
The following tabulation shows the employment for the
industry stratified by size (number of employees) of the unit:
E m p lo y m e n t s iz e
P e r c e n t d is tr ib u tio n
1 to 19 workers............................
20 to 49 workers..........................
50 to 99 workers..........................
100 to 249 workers.....................
250 workers or m o re..................
14.5
15,2
13.2
13.4
41.8
Fifty-eight percent of the employment in the security bro
kers and dealers industry was fairly evenly distributed among
the first four size groups. The remaining 42 percent was in
the units with at least 250 workers. The analysis that follows
shows that employment size is a key factor in determining a
unit’s staffing pattern.
Industry payrolls
The security brokers and dealers industry had the highest
payroll per employee of any industry in 1993.17 The average
weekly wage in this industry was $1,853, some 371 percent
of the economy-wide private sector average of $499. (In 1990,
the industry was the second highest paying, with an average
of $1,242 per week. The services allied with securities in
dustry (sic 628) had the highest pay in 1990 and the second
highest in 1993.) The high pay levels and their percent in
crease between 1990 and 1993 reflect how well the industry
has recovered from the downturn of the late 1980’s.
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Employment in the security brokers and dealers industry
is concentrated in relatively few States. Eight States (New
York, California, New Jersey, Massachusetts, Florida, Illi
nois, Texas, and Pennsylvania) accounted for 71 percent of
the total industry employment in 1993. Chart 3 shows each
State’s employment as a percentage of national employment
for the industry and for the United States as a whole. While
New York had only 7 percent of total U.S. private industry
wage and salary employment, it had almost 33 percent of all
employment in the security brokers and dealers industry.
California recorded the second highest share of industry em
ployment with 9 percent of the national employment. This
was, however, a smaller share than the 11 percent California
had of total employment in all industries.
Occupational employment
The data used for the analysis of occupational staffing pat
terns in the security brokers and dealers industry are from
the Occupational Employment Statistics (OES) survey.18 The
OES survey is a Federal-State cooperative survey of establish
ments that produces estimates of current occupational em
ployment by industry. The survey follows a 3-year cycle. In
the first year, manufacturing industries, hospitals, and agri
cultural services are covered, followed by mining, construc
tion, finance, and services industries in the second year.
Trade, transportation, communications, public utilities, and
education industries as well as State and local government
are surveyed in the third year. The survey is based on a prob
ability sample and is stratified by industry, geographic area,
and size (number of employees) of the unit.
The OES occupational classification system divides work
ers into seven major groups: managerial and administrative
occupations; professional, paraprofessional, and technical
occupations; sales and related occupations; clerical and ad
ministrative support occupations; service occupations; agri
culture, forestry, fishing, and related occupations; and pro
duction, construction, operating, maintenance, and material
handling occupations.
The 1993 OES survey shows that almost 99 percent of em
ployment in the securities industry was concentrated in four
of the major occupational groups: managerial, professional,
sales, and clerical. The data and analysis that follow relate
to these groups. The 3-year cycle for the security industry
resulted in data collected for 1984, 1987, 1990, and 1993.
Table 2 shows the resulting occupational estimates. May was
the reference month in each case. Thus, the 1987 data from
the OES survey reflect a period 6 months before the October
1987 stock market crash.
The end of the discussion for each occupational group
addresses the occupational distribution of workers by the
employment size of the establishment. The occupational es-
Monthly Labor Review
September 1995
23
Security Brokers and Dealers
timates for employment by size of the establishment are
shown in table 1.
ers, w h o m ust also be registered with the NASD, are discussed
under sales and related occupations.)
By the end of the 5-year bull market that began in 1982,21
firms had greatly increased their employment of managers.
Managerial workers
In 1984, the reported employment for this occupational group
This group includes top and middle managers, administrators, totaled 21,450. (See table 1.) By May of 1987 (approximately
and executives. They are responsible for policymaking, plan 6 months before the October crash), the number of managers
ning, staffing, and directing the activities of the establishment. had grown by 55 percent, reaching its highest level at 33,170.
The two managerial occupations with the greatest employment Their share of industry employment rose from 7.8 percent to
in the industry in 1993 were financial managers and general 9.6 percent over the 3-year period.
managers. Financial managers plan and direct financial ac
Although financial managers and general managers ex
tivities, including the investment strategies of the organization. perienced the largest percentage increases within this period
The general managers and top executives, who include broker (approximately 116 percent and 85 percent, respectively),
age managers, have diverse responsibilities that are not con notable percentage gains also occurred for managers direct
fined to a single functional area such as finance or marketing. ing other operations. The numbers of marketing, advertis
Many managers in this industry are designated by the ing, and public relations managers and personnel, training,
NASD as registered principals. They are defined as persons
and labor relations managers each grew by approximately 79
engaged in the management of a member’s investment bank-, percent.
ing or securities business. Their duties may include supervi
After the crash in 1987, firms began to reduce the number
sion and training. Registered principals are sole proprietors,19 of managerial positions in order to streamline operations. At
officers, partners, managers of offices of supervisory juris the outset, employment reductions were mainly of support
diction, and directors of corporations.20 Holders of these po staff, but in the first quarter of 1990, the industry reported its
sitions must pass the appropriate n a s d exam. (Sales manag worst profits in years and further cutbacks were inevitable.22
________
Chart
3. Share of U.S. security brokers and dealers employment and share of total private wage and salary
employment, eight States, 1993
Percent
35
Percent
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 35
□
Percent of security brokers
and dealers employment
Percent of private
industry employment
30
30
25
25
-
20
20
15
15
10
New York
24
California
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J
New Jersey
September
e
EIE
Massachusetts
1995
Florida
Illinois
Texas
Pennsylvania
-
10
-
5
By May of that year, the number of managers had declined by
slightly over 6 percent from the 1987 total. Decreases oc
curred mainly among purchasing managers, whose number
declined by 42 percent, and general managers and top execu
tives, for whom employment dropped by 22 percent.
Firms in the industry further trimmed their managerial
ranks from 1990 to 1993, even though, in the first half of
1993, net income for broker-dealers (doing public business,
as opposed to specialist firms that deal only with institu
tions)23 topped that for all of 1992. The industry showed a
managerial decline of 18 percent, and a decrease in manage
rial concentration to 7.3 percent from the 9.5 percent reported
in 1990. This drop, together with only a modest gain in in
dustry employment (325,230 to 349,880) over the same pe
riod, resulted in a decrease in the employment level of man
agers, from 31,050 to 25,360.
During this period, the employment levels of almost all
managerial occupations in the industry fell. The two largest,
financial and general managers, together accounted for 2,250
of the 5,690-worker decrease for all managers. Other func
tional managers such as mathematical managers,24 who de
creased in number from 1,350 in 1990 to 450 in 1993, expe
rienced much more severe relative effects of the downsizing
process. The number of marketing, advertising, and public
relations managers declined from 1,440 to 930, while em
ployment of personnel, training, and labor relations manag
ers decreased from 700 to 490.
Employment by size o f establishment, 1993.
Managers’
share of employment within a firm varied by the size of the
unit reporting, with the highest percentage in the smallest
employment size group. Within security brokers and dealers,
units with fewer than 20 employees had 13 percent of workers
in the managerial ranks. (See table 1.) General managers
made up 6.6 percent and financial managers comprised 6.1
percent of employment in these units. The units with wage
and salary employment between 20 and 49, between 50 and
99, and between 100 and 249 reported 6.4, 4.6, and 6.8
percent, respectively, of their workers as managers. Units
with more than 250 employees reported 7.3 percent of workers
as managers. These large units had a high percentage of
“specialized m anagers,” such as personnel managers,
marketing managers, or administrative services managers.
Professional and technical workers
Professional, paraprofessional, and technical workers within the
security brokers and dealers industry are involved in analysis,
trading, research, and advising. Substantial postsecondary edu
cation or on-the-job training usually is required for occupations
in this group. Persons in occupations concerned with the trad
ing of securities must be registered with the NASD. In 1993,
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security brokers, dealers, and flotation companies employed
54,380 professional workers, accounting for 15.5 percent of
industry employment. (See table 2.)
ost cutting measures within the industry over the study
period have included consolidations and intercompany
mergers of back office operations. The brokering and deal
ing of securities requires specially trained professional work
ers for functions such as the handling of computations, analy
sis, daily statements, regulatory reports, and settling and
clearing trades. Smaller units have often determined that it is
not cost-effective to have each of these specialized functions
performed by a professional on their payroll. Another cost
factor in the industry is that the operations require constant
implementation of more advanced technology.
Many of the smaller brokers and dealers use the greater
capacity of larger firms. Through a formal agreement, some
times called “outsourcing,” a smaller firm clears trades
through a larger firm. By outsourcing, a small firm can fo
cus solely on investing, while competing at the same level of
technology as larger firms. Some of the establishments with
excess back office capacity have found providing this service
profitable enough to create affiliates dedicated purely to do
ing so.
Clearing trades through other firms is not the only factor
that allows some units to conduct business with very few or
no professional workers. The bulk of computation, research,
and trading done within each firm is generally performed at
one central location. Other units may be front offices, em
ploying mostly registered representatives who deal directly
with clients.
Due to the aforementioned factors, only a small percent
age of establishments reported employing professionals, as
they are defined for this study. The 1993 employment level
for financial analysts was 6,380, yet only 10 percent25 of units
reported employment for this occupation. An estimated 4,950
accountants and auditors employed within the securities bro
kers and dealers industry were reported by 12 percent of the
units. Workers in computer science occupations totaled 9,850
within security brokers and dealers. Of these, systems ana
lysts and computer programmers were reported by 7 and 8
percent of firms, respectively. Credit analysts, budget ana
lysts, management analysts, and systems researchers each
were reported by approximately 2 percent of establishments
in the industry.
C
Employment trends, 1984-93. The overall industry demand
for this occupational group is illustrated by increases in its em
ployment level over the 1984-93 period. The amount of growth,
however, was largely a function of the profitability of firms.
Post-crash cost cutting and vital restructuring proved some oc
cupations to be more indispensable than others.
Monthly Labor Review
September 1995
25
Security Brokers and Dealers
Employment of professionals expanded rapidly from 1984
to 1987. The total number increased by 60 percent, from 27,720
to 44,490. These workers accounted for 24 percent of the over
all industry employment expansion during this period.
Professional occupations with rising employment levels for
the 1984-87 period were mainly concerned with financial and
operational analysis. Employment of statistical financial ana
lysts grew by 1,600 to total 5,300, and that of operations and
systems research analysts moved up by 1,230, to 1,490. The
number of accountants and auditors grew by 730 during this
time. Although the increase for accountants was not as great as
those for the aforementioned occupations, total occupational
employment for accountants was high in 1987, at 4,960 or 1.4
percent of industry employment. While there were large in
creases in the number of workers in professional occupations in
the 1984-87 period, the detailed professional occupations did
not all fare well in less prosperous markets.
Shortly after October of 1987, firms began cost cutting,
which included an employment reduction. Previously, total
industry employment had increased in almost every quarter.
Between 1987 and 1990, however, the total employment level
declined by slightly more than 5 percent, although the num
ber of professional workers grew by 6 percent to total 47,290.
The occupational share for these workers grew by approxi
mately 2 percentage points, such that professional workers
accounted for 14.5 percent of industry employment in 1990.
Restructuring did, however, trim employment of most ana
lytical positions. The residual occupational group of manage
ment support workers26 took the largest hit, dropping from 6,640
Table 2.
Percent distribution of workers by detailed occupation and establishment size class, security brokers
and dealers, 1993
1-19
workers
Occupation
20-49
workers
50-99
workers
100-249
workers
250
workers
or more
Managerial occupations..................................................
Financial managers.....................................................
General managers (brokerage managers)................
13.04
6.14
6.55
6.40
1.86
4.15
4.62
1.2
2.13
6.76
1.59
3.19
7.27
2.31
1.70
Professional occupations................................................
Accountants and auditors..........................................
All other financial specialists.......................................
Systems analysts, electronic data processing..........
Computer programmers..............................................
Financial analysts, statistical.......................................
Economists, including market researchers................
Public relations specialists..........................................
3.75
.85
.55
.17
.11
1.10
.14
.02
5.07
.51
.86
.15
.21
1.83
.06
—
6.00
.59
1.54
.28
.10
2.23
.24
—
8.59
.87
1.01
.42
.69
1.32
.36
.07
27.91
2.53
8.70
2.03
3.24
1.72
1.06
.11
Sales and related workers..............................................
First-line supervisors...................................................
Sales agents—security, commodity,
and financial services...............................................
46.33
1.80
54.15
1.03
60.16
1.73
50.34
1.73
18.72
.74
42.9
50.84
55.64
43.12
14.63
Clerical and administrative support workers..................
First-line supervisors...................................................
Brokerage clerks..........................................................
Secretaries...................................................................
36.09
3.53
17.64
6.17
34.34
2.29
11.46
11.51
29.07
1.12
10.36
7.34
34.01
2.10
11.60
5.89
44.27
3.85
14.48
6.95
N ote : Dash indicates no data, or data not available.
26
workers to 2,210, for a 67-percent decrease. Employment of
management analysts declined by 300 to total 410. The num
ber of operations and systems analysts, except computer,
dropped by 380 to 1,110 in 1990, and that of economists de
clined by 270, to 1,570 workers. The employment of statistical
financial analysts, however, barely changed (a 30-worker in
crease); this group numbered 5,330 in the latter year.
By May of 1993, the market had recovered and firms
reconfigured staffing patterns accordingly. In the first half of
the year, the industry saw an increase in mergers and acqui
sitions, as well as highly profitable Initial Public Offerings.27
With increasing momentum, firms picked up employment of
statistical financial analysts, raising the level by 1,050 work
ers to total 6,380. Also, the employment level for economists
rose to 2,040, surpassing its 1987 level.
Professional workers dealing with internal operations de
clined in employment between 1987 and 1990. The group of
accountants and auditors, which had grown by 12 percent
from 1987 to 1990, declined almost an equal percent (11)
between 1990 and 1993. The employment level for manage
ment analysts, which had fallen over the 1987-90 period,
changed little. The number of operations and systems ana
lysts, except computer, dropped to a mere 350 workers, a 68percent decline over 3 years.
The most dramatic employment change throughout the
four survey rounds examined is the increase for “all other
financial specialists.” This occupation is a residual within
the oes structure. Firms report employment in this category
for financial occupations not individually specified. This
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September
1995
financial specialists” (that is, traders, including those as
signed to exchange floors) each made up around 1 percent of
industry employment. In contrast, units that employed at
least 250 workers had 27.9 percent of their workers in the
professional group. These units also employed the financerelated occupations in greater percentages. In addition, the
larger units reported the majority of the employment of com
puter related workers, economists, labor relations specialists,
and lawyers within the industry. The fact that employment
for these occupations in the smaller firms is low is partly due
to the concentration of such jobs in centralized departments
in multi-location firms, as well as to outsourcing.
Sales and related workers
residual occupation includes traders.28 The occupation to
taled 1,720 workers in 1984 and had increased, by 256 per
cent, to 6,120 in 1987. It more than doubled to 13,560 in
1990, and then rose another 25 percent, to 17,000, in 1993.
Because this residual occupation is composed of various fi
nancial specialists, it is difficult to link its increase to any
specific factors.
The number of computer scientists and related workers
within security brokers and dealers increased more than 63
percent from 1984 to 1993. Within this occupational group,
the employment level of systems analysts was at its highest
in 1990, with 4,090 workers. That level had declined to 3,080
by 1993. Total growth for this occupation during all four
survey rounds amounted to 41 percent. For computer pro
grammers, the overall increase between 1984 and 1993 was
47 percent. Their employment totaled 3,440 in 1984, peaked
at 5,680 in 1987, and then declined slightly to 5,040 in 1993.
Employment by size o f establishment, 1993. Size of estab
lishment data from 1993 show that the percentage of profes
sional workers in security brokers and dealers increases with
unit employment. In establishments with fewer than 20 em
ployees, 3.8 percent of workers were professionals. (See table
2.) Occupations related to finance, including financial ana
lysts, accountants and auditors, and the residual “all other
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Any employee of a firm who participates in the business of
investment banking or securities transactions, including ac
count solicitation, must be recognized by the NASD as a reg
istered representative.29 To qualify, an employee must first
be sponsored by a member firm. The association performs
an investigation of the applicant for involvement in any vio
lation of Federal or State laws, or n a s d or exchange rules.
Applicants must pass the exam appropriate for the securities
brokered, and can then engage in the solicitation of instru
ments for which they are qualified. Supervisors of these
workers are considered principals, and must pass the NASD
exam that pertains to the securities solicited by themselves
and their workers. In the security brokers and dealers indus
try, the oes occupation “sales agents—securities, commodi
ties, and financial services” is made up largely of brokers.
Brokers are generally paid on a commission basis. Each
firm formulates a grid, with payments determined by both
the price and number of shares traded. Every trade produces
a commission, of which a percentage is identified as broker
earnings. The Securities Industry Association reported in
1994, however, that a “growing number of firms are chang
ing compensation practices, paying brokers by portfolio per
formance, assets managed, or other alternatives.”30
The employment level for these sales agents or brokers
did not decline through any of the survey rounds. In fact,
their number increased dramatically between 1984 and 1987,
from 89,100 to 103,210. (See table 2.) Between 1987 and
1990, however, the level barely changed. This was contrary
to the experience of the overall industry, which lost 5 percent
of its employment in the aftermath of the 1987 crash.
By 1993, the employment of “sales agents—securities,
commodities, and financial services” reached 122,500, an 18percent rise from 1990. Although stock prices plummeted
again towards the end of 1990, the following year brought
low interest rates and favorable investing conditions. By
1993, average daily trading volume on the majority of ex
changes had increased substantially. Because the number of
Monthly Labor Review
September 1995
27
Security Brokers and Dealers
trades is a key determinant of commissions, the favorable
market conditions brought greater earnings potential for bro
kers.
While the percentage fluctuations in employment for sales
agents (mostly brokers) in the industry tended to correspond
with overall market performance over the study period, the trend
of their earnings (commissions) was an even better match. (See
chart 4.) Between 1984 and 1987, the employment level of
these workers rose by 15.8 percent. Over the same period, com
missions increased from $7.095 billion to $12.67 billion, an
increase of 78 percent. Between 1987 and 1990, when employ
ment grew by only 0.5 percent, broker commissions declined.
By 1990, commissions had fallen about 13 percent from the
1989 level, which in turn was down 20 percent from 1988.31
The total drop in commissions for the 1987-90 period was 30
percent ($12.674 billion to $8.878 billion).
By 1993, both the employment and commissions of the.
industry’s brokers had surpassed pre-crash levels. Occupa
tional employment was up 18 percent over the 1990 level,
totaling 122,150. Commissions had risen to $13.707 billion,
a 54.4-percent increase from the previous survey round.
From 1984 to 1993, the movement of broker commissions
as a percent of total revenues was inverse to that of broker em
ployment as a percent of industry employment. (See chart 4.)
Highs and lows for this period occurred in 1987, when com
missions accounted for 24.93 percent of total revenues and in
1990, when they accounted for 16.43 percent. In contrast to the
commission ratio, broker employment comprised its highest
percentage in 1993, and its lowest in 1987, when the occupa
tion accounted for 30.1 percent of industry employment.
comparison of data for 1984 with those for 1993
reveals that the decline of com m issions as a per
cent of total revenues was almost equal to the increase of
brokers as a percent of industry employment. In 1984, com
missions amounted to 22.73 percent of total revenues and
brokers accounted for 32.6 percent of industry employment.
By 1993, commissions accounted for 19.21 percent of total
industry revenues, and brokers, 35.01 percent of total indus
try employment.
From 1984 to 1987, the employment level of sales super
visors moved inversely to that of the workers they supervised.
The level decreased between 1984 and 1987, from 5,500 to
5,020, but then grew dramatically through 1990, to total
7,684. By 1993, the number of sales supervisors had fallen
to 4,410. This fluctuation may be due to the interchanging of
supervisory and front-line sales jobs.
A
Employment by size o f establishment 1993. Employment
staffing patterns show that units with fewer than 20 employ
ees had 46.3 percent of their workers in sales. (See table 2.)
The 60.2 percent of sales workers in establishments employ
28
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September
1995
ing 50 to 99 workers was the highest concentration of such
workers in any establishment-size group. In units employing
20 to 49 workers and 100 to 249 workers, sales occupations
accounted for 54.2 and 50.3 percent of total employment, re
spectively. In contrast, the largest firms, with 250 or more
employees, had only 18.7 percent of their workers in sales.
Large establishments provide in-house or outsourced back
office operations, and trading and research departments.
Because these activities require large numbers of professional
and clerical staff, the sales worker share of total firm employ
ment is lower.
Clerical workers
Advances in equipment, including computers, have increased
the productivity of the industry’s clerical workers. Previously,
brokers were required to pass a ticket for each order to a wire
operator, who keyed the order into a processing system that
sent it to an exchange. Now, some order entry systems allow
brokers to input trades as they are requested, directly from
their desks. The process takes about 1 minute as opposed to
10 minutes under the old system. The efficiency of the cur
rent system is such that market transactions often can be com
pleted before a security experiences any movement in price.
Electronic trading systems transmit orders directly to a re
ceiving unit. Both advances eliminate paper tickets, and thus
the need for clerks to handle them.
Electronic systems allowed management to trim the em
ployment of clerical workers to 36.9 percent of the total in
1993, down from 42.6 percent in 1984. (See table 2.) In
1984, there were 116,930 clerical workers employed by secu
rity brokers and dealers. By 1987, employment in the indus
try as a whole had grown by almost 22 percent, and the num
ber of clerical workers had risen by almost 28 percent, to
142,200. Between 1987 and 1990, however, industry em
ployment declined by about 5 percent, while the number of
clerical workers fell by more than 19 percent, to 119,930. By
1993, when total industry employment had risen by more than
8 percent from its 1990 level, there were 129,140 clerical
workers, also an increase of 8 percent.
The clerical occupation that experienced the sharpest de
cline in share of industry employment between 1984 and 1993
was secretaries, whose numbers fell from 9.8 percent to 7.4
percent of the total. Furthermore, while 73 percent of firms
reported employing secretaries in the 1987 survey, only 57
percent reported such employment in 1993. While secretar
ies still are one of the most numerically significant clerical
occupations, more firms are able to provide their customers
services without having someone designated to perform tra
ditional secretarial duties. In some units, these duties have
been assigned to other workers such as receptionists and in
formation clerks, whose numbers increased from 2,360 to
4,460 over the 1987-93 period.
While there has been a decline in numbers of clerical work
ers as technological advances are further implemented, clerical
jobs are not disappearing as quickly as the paperwork. Many
firms are altering the tasks performed by these workers so that
the difference between their work and that of other occupational
groups is less clearly defined. In addition, many clerical work
ers are being assigned to trading desks, where they are being
retrained for work of a more professional nature.32
Employment by size o f establishment, 1993. In 1993, cleri
cal workers were most abundant in offices with more than
250 workers. Their 44.3-percent share of employment (table
2) is attributable to the back office operations located in these
establishments. In addition to brokerage, accounting and
auditing, and general office clerks, large establishments also
employed greater percentages of statistical and adjustment
clerks. Units with fewer than 20 workers employed the sec
ond greatest percentage of clerical workers (36.1 percent).
Included were large numbers of brokerage clerks, secretar
ies, and general office clerks.
T he se c u r ity br o k er s a n d d e a l er s industry witnessed a
major overhaul in the way that business was conducted over
the 9-year period ending in 1993. The technological changes
introduced affected both the staffing patterns of firms and the
tasks performed by workers in various occupations. The re
sult is an industry that today encompasses greater shares of
professional and sales occupations, and relatively fewer mana
gerial and clerical occupations, than in the past.
□
Footnotes
1 S ta n d a r d I n d u s tr ia l C la s s ific a tio n M a n u a l (U.S. Office of Management
and Budget, 1987).
b y th e ra tio o f fu ll- t im e to p a r t-tim e w o rk ers as w e ll a s th e n u m b er o f
in d iv id u a ls in h ig h -p a y in g and lo w -p a y in g o cc u p a tio n s.
2 Na s d a q I n v e s to r S e r ie s , The NASDAQ I n v e s to r G lo s s a r y (The National
Association o f Securities Dealers, Inc. ( n a s d ) , December 1992), p . 6 .
18 H a n d b o o k o f M e th o d s, B u lle tin 2 4 1 4 (B u reau o f L ab or S ta tistics, 1 9 9 2 ),
pp. 2 9 - 3 1 .
3 An explanation o f the
September 1994.
n a sd
registration and examination requirements,
4 The n a s d a q Stock Market, Inc., “The future o f intelligent trading
here...” (The n a s d a q Stock Market, Inc., 1994).
is
5 Bureau o f Labor Statistics es-202 program, unpublished data.
6 The “Quarterly Dow Jones Industrial Stock Averages” in this passage are
the closing average for the month stated. Fluctuations were calculated using
the two time frames stated, not a compilation o f all quarters in-between. See
B a r r o n ’s N a tio n a l B u sin e ss a n d F in a n c ia l W eekly, various issues, 1993.
7 S ta n d a r d a n d P o o r s In d u s try S u rv e ys, Apr. 13, 1989, p. 1-43.
8 n y s e firms’ income statement. Source: Securities Industry DataBank.
9 The pretax profit data in this section is from the
statement.
n y se
firms’ income
10 Bureau o f Labor Statistics es-202 program, unpublished data.
11 Ibid.
12S ta n d a r d a n d P o o r s In d u s try S u rv e ys, July 12, 1990, p. 1—40.
13 S ta n d a r d a n d P o o r s I n d u s try S u rv e y s , Nov. 3, 1994, p. B-55.
14 Ibid
15 Ibid.
16n y s e firms’ income statement. Source: Securities Industry DataBank.
17 b l s 1993 Employment and Wages Annual Averages. The reference to
any industry is at the 3-digit sic level. The weekly wage number is derived
by dividing the total annual pay o f employees covered by unemployment
insurance programs by annual average employment. A further division by
52 yields average weekly wages per employee. Average wages are affected
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19 S o le proprietors are n o t in clu d ed in the em p lo y m e n t data fo r th is article.
20 A n ex p la n a tio n o f the
S ep tem b er 1 9 9 4 .
n a sd
reg istra tio n and ex a m in a tio n requ irem en ts,
21 S ta n d a r d a n d P o o r s I n d u s try S u rv e y s , Apr. 3 , 1 9 8 9 , p. 1 -4 3 .
22 S ta n d a rd a n d P o o r s In d u s try S u rv e y s , Ju ly 12, 1 9 9 0 , p. 1 -4 0 .
23 S ta n d a rd a n d P o o r s I n d u s try S u rv e y s , N o v . 18, 1 9 9 3 .
24 T h e actual o e s title fo r th is o cc u p a tio n is “en g in ee rin g , m ath em a tica l,
and natural s c ie n c e s m a n a g ers.” G iv e n the se r v ic e s p ro v id ed b y this industry,
it is a ssu m ed that the reported e m p lo y m e n t is fo r the m a th em a tica l m an agers.
25 T h e p ercen t o f firm s reportin g e a c h o cc u p a tio n is p ro d u c ed w ith the o e s
estim a tes. D u e to sp a c e lim ita tio n s, th is n u m b er is n o t s h o w n in th e ta b les in
this article.
26 T h e o e s o c c u p a tio n stru ctu re in c lu d e s “a ll o th er” o c c u p a tio n s that a llo w
r e s p o n d e n ts to re p o r t e m p lo y m e n t fo r w o r k e r s n o t c o v e r e d w ith in th e
d e fin itio n fo r a n y o f th e s p e c if ie d d e ta ile d o c c u p a tio n s . In o rd er to o b ta in
in fo rm a tio n o n th e co n te n t o f th e s e “a ll o th er” o r re sid u a l o c c u p a tio n s , the
o e s p ro g ra m
is cu rren tly im p le m e n tin g a p la n to d is a g g r e g a te resid u a l
o c c u p a tio n s o n th e su r v e y fo rm s.
27 S ta n d a rd a n d P o o r s I n d u s try S u rv e y s , N o v . 18, 1 9 9 3 , p. B -6 4 .
28 Traders, lik e p rin cip a ls and brok ers, m u st b e reg istered w ith the
29 A n ex p la n a tio n o f the
S ep tem b er 1994.
n a sd
n a sd
.
reg istra tio n and ex a m in a tio n requ irem en ts,
30 S ecu rities Industry A ss o c ia tio n , M e d ia R e le a se N o . 5 1 6 , A u g . 8, 1 9 9 4 .
31 S ta n d a r d a n d P o o r s I n d u s try S u rv e y s , D e c . 5 , 1 9 9 1 , p. 1 -4 2 .
32 W all S tr e e t a n d T ech n o lo g y, v o l. 11, n o. 13, pp. 5 5 - 5 8 .
Monthly Labor Review
September 1995
29
Trends in unemployment
insurance benefits
The share o f the unemployed receiving
unemployment insurance declined slowly, but consistently,
starting in the 1940’s, dropped dramatically
during the 1980-84 period, and remains low
Daniel P. McMurrer
and
Amy B. Chasanov
he Federal-State unemployment insur
ance (Ul) system, created in 1935, was
designed to provide temporary wage re
placement for unemployed workers who have
demonstrated a strong attachment to the labor
force and to assist in stabilizing the national
economy during cyclical economic downturns.
The nature of the system assigns different re
sponsibilities to the Federal and State govern
ments. Although broad Federal laws ensure con
sistency in areas where uniformity is considered
essential, States determine most of the details of
program operations and administration. As a re
sult, many features of the system vary greatly
among States.
T
Insurance programs
Daniel P. McMurrer
and Amy B. Chasanov
are policy analysts at
the Advisory Council
on Unemployment
Compensation.
30
Two separate, but interrelated, programs cur
rently provide income support to qualified un
employed workers: the permanent, regular, State
ui programs and the Federal-State Extended
Benefits program. In addition, during every re
cession since 1958, emergency supplemental Ul
benefit programs have been enacted by Congress
on an ad hoc basis. The characteristics of the
three components of the Ul system are discussed
in more detail below.
Regular State unemployment insurance. Regu
lar State Ul programs generally provide up to
26 weeks of benefits to qualified unemployed
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Federal Reserve Bank of St. Louis
September 1995
workers. The eligibility of an unemployed
worker is determined by State laws regarding
monetary factors (such as recent earnings his
tory) and nonmonetary factors (such as the rea
son for separation from employment and cur
rent availability for work). The duration and
amount of benefits for eligible individuals are
based primarily on an individual’s recent earn
ings history.
State taxes on employers1finance most benefits
paid by the program.2Tax rates vary among em
ployers in the same State and are based partially
upon the level of past Ul claims that were made by
an employer’s former employees. Federal taxes
imposed by the Federal Unemployment Tax Act
pay for the administration of State Ul programs
and the Federal share of the Extended Benefits
program. The total amount paid by the regular
program is cyclical with the level increasing as
the number of unemployed increase during peri
ods of economic downturn. In 1993, more than
$22 billion was paid in regular benefits.
Federal-State Extended Benefits. The FederalState Extended Benefits program provides up to
13 additional weeks of benefits to individuals
who have exhausted their regular ui benefits.
Half of the cost of extended benefits is financed
by the Federal government and half is paid by
the State distributing the benefits. Extended
Benefit amounts are the same level as the State’s
regular benefits.
Extended Benefits are available only when a measure—
usually, the Insured Unemployment Rate—of State unem
ployment rises above a particular level. Most States currently
use the insured unemployment rate as the only “trigger” for
the program. Because this rate is determined by the number
of regular Ul claimants in a State, eligibility for extended
benefits in most States is affected directly by States’ Ul eligi
bility laws. As a result, a decline in the percentage of the
unemployed who receive regular ui benefits has contributed
directly to a drop in the number of States in which Extended
Benefits are available.
Emergency benefit programs. The Emergency Unemploy
ment Compensation program is a temporary benefits pro
gram that the Congress enacted in November 1991 and ex
tended on several occasions. The Congress allowed the pro
gram to expire in February 1994. This emergency compen
sation program was similar in many ways to several previ
ous emergency programs, which the Congress enacted dur
ing recessions. For example, the Federal Supplemental Ben
efits program paid benefits between 1975 and 1978, and the
Federal Supplemental Compensation program paid benefits
between 1982 and 1985.
The number of additional weeks of benefits that were
available in the Emergency Unemployment Compensation
program depended on three factors: when the claimant first
applied for these benefits, a State’s unemployment rate, and
the national unemployment rate. Claimants for Emergency
Unemployment Compensation were required to meet their
State’s eligibility criteria, in addition to Federal require
ments recompensation while it operated.
Because the Federal Government finances all the costs of
emergency unemployment benefits, but only 50 percent of
Extended Benefits costs, States took advantage of the option
to provide Emergency Unemployment Compensation. Fol
lowing the most recent recession, the Emergency Unemploy
ment Compensation program nearly replaced the Extended
Benefits program entirely (payments of extended benefits
since 1991 have been less than $400 million). In total, the
Emergency Unemployment Compensation program cost
more than $26 billion; a significant proportion was financed
out of general government revenues.
The unemployed
Characteristics of the unemployed differ slightly in compari
son with the civilian labor force. (See table 1.) In particular,
younger individuals, men, and blacks are disproportionately
represented among the unemployed. Individuals who seek
ui benefits tend to be older than unemployed workers in gen
eral; men also are disproportionately represented.
The percentage of Ul claimants who have exhausted their
regular benefits during recessions has increased in most re
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cessions since 1970. Similarly, the average duration of un
employment spells has increased, as has the percentage of
individuals who have been unemployed for particularly long
periods. The number of job losers on layoff has increased,
while the percentage of the unemployed who are new en
trants to the labor force has decreased.
Trends in regular State ui programs
The regular Ul system can be examined, using several mea
sures: the percent of the labor force that is covered under the
ui program; standards regarding eligibility for ui benefits
among the unemployed; the amount of ui benefits received;
the duration of the benefits; and the percentage of the cov
ered population that receives ui benefits.
Coverage. The percentage of the work force covered by the
(workers whose employers pay ui taxes on their
wages) has increased. (See chart 1.) The most recent signifi
cant increases in coverage were legislated in the 1970’s, when
several groups, including State and local government em
ployees, many household workers, and employees of small
businesses, were covered for the first time. Now, ui coverage
is nearly universal, extending to more than 90 percent of ci
vilian employment in the United States. This includes nearly
all wage and salaried workers, representing 106 million em
ployees. The only major groups that currently remain uncov
ered are workers on farms defined as “small,” and the selfemployed.
ui system
Eligibility. Eligibility criteria for ui benefits vary among
States. However, three general principles apply in all States:
individuals must earn a certain minimum amount in a par
ticular period to be eligible; eligible individuals must be avail1 Characteristics of the labor force and recipients of
unemployment insurance, 1993
[In percent]
C h a ra c te ris tic s
C iv ilia n
la b o r fo rc e
To tal
u n e m p lo y e d
U n e m p lo y m e n t
in s u ra n c e
c la im a n ts
Age:
16 to 3 4 ..........................
35 to 5 4 ..........................
55 and o v er...................
43
45
12
58
34
8
42
46
12
Gender:
Men................................
Women ..........................
54
46
56
44
60
40
Race:
W hite.............................
Black..............................
O th er.............................
85
11
4
75
21
4
N ote :
_
_
-
Dash indicates data are not available.
S ource: U.S. Department of Labor, Bureau of Labor Statistics (1994) and
unemployment Insurance data.
Monthly Labor Review
September 1995
31
Unemployment Benefits
able and able to work, and, accord
ing to requirements of most States,
must actively seek work; and eligible
individuals must have lost their jobs
due to no fault of their own. This lat
ter requirement tends to exclude most
employees who quit their jobs and in
dividuals who have been fired for
cause.
A lthough many State policy
changes have restricted eligibility, in
dividual wages have simultaneously
increased as a result of inflation, al
lowing more individuals to reach the
minimum earnings threshold. Esti
mates suggest that these two trends
have nearly canceled out one another,
with eligibility remaining fairly con
stant at approximately 43 percent of
the unemployed.3
C h a rt 1.
Percent
Work force with unemployment insurance coverage, as a percent
of the work force, 1947-93
Percent
Level o f benefits. State formulas
based on previous recent earnings
determine the weekly benefit amount
1947 1951 1955 1959 1963 1967 1971 1975 1979 1983 1987 1991 1993
for eligible individuals. Each State
has minimum and maximum levels
SOURCES: Council of Economic Advisers (1994) and Bureau of Labor Statistics(1994)
of weekly benefits. For individuals
not eligible for the maximum amount,
weekly benefits in most States are ap
proximately 50 percent of some measure of his or her previ economic downturns by automatically injecting more money
ous weekly earnings. The average amount received by work into the economy during periods of high unemployment. The
insured unemployment rate is the primary method that acti
ers in 1993 was approximately $180 per week.4
vates the Extended Benefits program during recessions. Be
Duration o f benefits. In most States, the potential duration cause the decline in the percentage of recipients is reflected in
of ui benefits also is based on an individual’s recent earn the insured unemployment rate, the decline also has had the
ings.5 Maximum duration is uniform among States; all but effect of weakening the countercyclical effectiveness of the Ex
two provided a maximum of 26 weeks of benefits in 1993.6In tended Benefits component of the UI system.
The two declines have likely been caused by a combina
general, the average potential duration of benefits has in
creased gradually, as has the average duration of unemploy tion of factors that tend to have similar effects on the UI sys
tem. The long-term decline is probably a partial result of
ment spells. (See chart 2.)
broad shifts in labor market demographics, with industrial
shifts such as the decline in manufacturing, and increases in
Trends in receipt of ui benefits
ui coverage. To the extent that the percentage of the unem
Two trends have become apparent in the ui benefits program. ployed who receive UI benefits has decreased over the long
The percentage of the unemployed who receive UI benefits term, the UI program no longer responds to the needs of a
(referred to as “recipiency”) has declined slowly, but consis growing portion of the unemployed population.
Several researchers have identified the causes of the re
tently, since the 1940’s; and the percentage of recipients has
dropped dramatically between 1980 and 1984 and has re cent, more short-term decline in recipiency nationwide. Four
mained at a low rate throughout the 1980’s and early 1990’s. factors have been identified as the primary causes, although
These declines are of considerable concern. They threaten to the results have not been wholly consistent and research
undermine the two primary functions of the UI system: partial ers have had substantial difficulty in separating the effects
replacement of wages for unemployed workers, and countering fully.
32
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Federal Reserve Bank of St. Louis
September 1995
First, policy changes were made on the Federal and State
levels that appear to have reduced the percent of the unem
ployed who receive benefits. Second, an increasing percent
age of the unemployed live in States in which the percent of
the unemployed who receive benefits is consistently below
the national average. Third, the unionized percentage of the
work force, in which rates of ui claims have historically been
high, has declined. Fourth, the percentage of the work force
employed in the manufacturing sector, in which rates of UI
claims also have been high, has declined.
Who receives benefits?
Two primary statistics that generally measure recipiency are
the ratio of the insured unemployment rate to the total unem
ployment rate,7 and the ratio of UI claimants to the total num
ber of unemployed.8The two ratios are highly correlated. (See
chart 3.) The ratio of the insured unemployment rate to the
total unemployment rate is more difficult to interpret than
the ratio of UI claimants to the total number of unemployed
because of various mathematical complications related to the
definitions of the populations that are counted. This can re
sult in a measure that is above 100 percent. Still, the ratio of
insured unemployment rate to the total unemployment rate
C h a rt 2.
ratio is widely reported, and the insured unemployment rate
is particularly important because it represents the primary
trigger for the Federal-State Extended Benefits program.
Both ratios are based on a measure of the number of UI
claimants, which is collected weekly by States. The total num
ber of claimants, however, includes some individuals who do
not receive UI benefits but are counted among the insured un
employed for a particular week. Three primary groups of indi
viduals fall into this category: individuals who are on a 1-week
waiting period before they begin to receive benefits; claimants
who ultimately are denied benefits for nonmonetary reasons;
and claimants who are disqualified from collecting benefits in
a particular week for reasons that include the requirements
that recipients be able and available for work and that claim
ants who are working do not exceed a particular level of in
come in a week. Including these groups has tended to inflate
the measure of UI recipiency by 10 to 15 percent per year.
Trends and implications
Both recipiency measures have shown a long-term decline
and a more short-term decline. (See chart 3.) The measures
also vary considerably across States: in 1993, the ratio of
claimants to total unemployed ranged from 15 percent in
Duration, in weeks, of unemployment spells and maximum potential duration, in weeks, of
unemployment insurance benefits, 1950-93
Number of weeks
Number of weeks
1950
1954
1958
1962
1966
1970
1974
1978
1982
1986
1990
NOTE: The 1979 figure for duration of benefits was interpolated and substituted for erroneous data.
SOURCES: Council of Economic Advisers (1994) and U.S. Department of Labor (1994).
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
Monthly Labor Review
September 1995
33
Unemployment Benefits
South Dakota to 64 percent in Alaska. (See table 2.) An addi
tional measure, the ratio of ui claimants to total job losers,
also has demonstrated long-term and short-term declines.
(See chart 4.)
In an analysis of the characteristics of unemployed indi
viduals who were not receiving benefits, the Congressional
Research Service found that they were typically young, did
not head families, and were not the primary source of income
in their families. Generally, they have lower-than-average in
comes before and after unemployment. However, only 42 per
cent of those who were employed full-time for 1 year before
the start of their unemployment spell received benefits.9
total unemployment rate and the ratio of ui claimants to the
total number of unemployed declined sharply in the early
1980’s. By 1984, the number of unemployed collecting ui as
a percentage of total unemployment had dropped to 28.5 per
cent, the lowest recorded percentage since 1947, when such
data were first collected. The ratio has increased slightly since
1984, but has remained lower than its historical average. The
period of the early 1980’s was the first during which the ratio
of ui claimants to the total number of unemployed did not
increase significantly as the unemployment rate peaked. (See
chart 5.) This represents a fundamental shift from the dy
namic trends that had marked the ui program since its incep
tion.10 Gary Burtless and Daniel Saks noted that the strong
Long-term trends. In the long term, the ratio of insured un and stable statistical relationship between the number of ui
employment rate to total unemployment rate has dropped claimants and number of job losers ended in the early 1980’s.11
approximately 60 percent since 1947, and the ratio of ui
The declines in recipiency are potentially significant for
claimants to the total number of unemployed has declined several reasons. First, they threaten to undermine the capac
approximately 40 percent over the same period. These trends ity of the ui system to provide partial wage replacement for
suggest that the UI program has been serving an ever-decreas unemployed workers and to counter economic downturns by
ing percentage of the unemployed, with periodic increases dur automatically pumping more money into the economy dur
ing recessions. This was largely the result of recessionary in ing periods of high unemployment. The effectiveness of the
creases in the percentage of the unemployed who are job losers. system in performing these two roles is a direct function of
the percentage of the unemployed whom the program serves.
Short-term trends. In addition to the long-term decline in
Furthermore, the decline of the insured unemployment rate
recipiency, the ratio of the insured unemployment rate to the relative to total unemployment has weakened the countercyclical
effectiveness of the ui system: the insured
Chart 3.
unem ploym ent rate is the prim ary
Measure of recipients in regular State UI programs, 1947-93
mechanism to activate the Extended
Benefits program during recessions.
Thus, the decline in the insured unem
ployment rate has resulted in a signifi
cant reduction in the number of States
in which extended benefits are available.
The long-term decline
Research suggests that the long-term de
cline is primarily a result of changes in
the demographic composition of the la
bor force and that the decline in one mea
sure (the ratio of the insured unemploy
ment rate to the total unemployment rate)
is partially the result of increases in ui
coverage.
SOURCES: Council of Economic Advisers (1994) and U.S. Department of Labor (1994).
34
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Federal Reserve Bank of St. Louis
September 1995
Broad demographic changes. A pri
mary cause of the decline in the ratio of
ui claimants to the total number of un
employed before 1980 was the chang
ing demographic composition of the
jobless, according to B urtless and
S aks.12 Throughout the 1960’s and
1970’s, as many women and young
workers from the baby-boom generation entered the labor
force, they also made up a higher percentage of the unem
ployed. As a result, men of prime working age, who are the
most likely to receive Ul benefits, declined considerably as a
percentage of the unemployed. Burtless and Saks found that
such demographic changes explain a large percentage of the
decline in the ratio of Ul claimants to the total number of
unemployed before 1980.
While the impact of demographic changes described by
Burtless and Saks declined after 1980, other demographic
changes have continued or even accelerated in the 1980’s
and 1990’s. Perhaps the most significant change is the con
tinuing increase in the number of two-earner families. Al
though empirical research has not addressed this issue, the
increase in two-earner households has most likely reduced
the need among some workers to apply for ui benefits when
they become unemployed. Thus, it is possible that various
broad demographic changes continue to have a negative im
pact on the rate of ui recipiency.
Increases in U l coverage. Newly covered employees in the
1970’s were probably less likely to apply for ui compensation
than previously covered groups.13 As a result, the insured un
employment rate (the number of ui claimants as a percentage of
jobs covered by Ul), declined because of the increased coverage
of the system. Burtless and Saks suggest that the insured unem
ployment rate may have declined by between 0.5 and 0.8 per
centage points because coverage was extended twice in the
1970’s.14 Such a decline would account for a large percentage
of the decline in the ratio of the insured unemployment rate to
the total unemployment rate in this period, although it would
not be expected to have the same effect on the ratio of ui claim
ants to the total number of unemployed.
Decline in manufacturing. Burtless and Saks also identified
the shift of workers from manufacturing and other industries
with high recipiency rates as a primary cause of the long
term decline in the number of recipients. They report that
estimating with precision the magnitude of this effect is diffi
cult. The decline in manufacturing also has been identified
as a significant cause of the decline during the 1980’s.15
The short-term decline
Research examining the decline in ui recipiency that occurred
in the early 1980’s continues to be inconsistent. The variability
of the results is an indication of the difficulty researchers have
had quantifying the impact of the four factors identified earlier:
changes in Federal and State policy, population shifts, declin
ing unionization rates and the decline in manufacturing. A com
bination of some or all of these factors probably contributed
significantly to the short-term decline.
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Federal Reserve Bank of St. Louis
Policy changes. During the 1980’s, several changes in Fed
eral and State law appear to have contributed to the drop in
the percentage of the unemployed who received unemploy
ment benefits. Overall, the Federal General Accounting Of
fice found that policies designed to improve the solvency of
State trust funds reduced the recipiency among unemployed
individuals.16 Most significantly, numerous State laws were
changed to restrict eligibility and reduce benefit levels, partly
in response to Federal policies that encouraged States to adopt
more restrictive legislation for regular State unemployment
programs. Several Federal laws, most notably the decision to
tax ui benefits, also directly reduced the value of unemploy
ment benefit levels.
Federal policies. During the 1980’s, Federal regulations gov
erning State Ul trust funds were changed significantly. Be
ginning in 1982, States were required to repay with interest
Federal loans to their trust funds. Previously, the loans were
interest-free and repayment requirements were unclear. States
with loans also were required to adopt other specific mea
sures to ensure solvency.
Overall, these changes provided incentives to States to
avoid the need for future loans by reducing the scope of State
programs. In addition, States were given other direct incen
tives, linked to Federal Extended Benefits funds, to tighten
ui eligibility requirements and to reduce ui benefits. Taken
as a whole, State policy reflected these changes in Federal
policy. Federal laws also were changed in ways that directly
affected the recipiency rate. In 1979, ui benefits for the first
time were partially taxed, and in 1986, all unemployment
benefits became subject to taxation. States also were required
to reduce or eliminate ui payments to unemployed workers
who received pensions or Social Security payments. Walter
Corson and Walter Nicholson found that, overall, between
11 percent and 23 percent of the total decline can be attrib
uted directly to various Federal policy changes. Specifically,
between 11 percent and 16 percent of the decline is due to
partial taxation of benefits and up to 7 percent is the result of
less generous Extended Benefits programs.17
State policies. The GAO reported that, between 1981 and
1987,44 States adopted tighter monetary eligibility standards
or stricter disqualification provisions for their regular ui pro
grams. Many of these State changes probably were the result
of Federal incentives to tighten eligibility, although deter
mining the precise impact that changes in Federal legisla
tion alone had on the policy decisions of States is impossible.
Some research has found that these and other changes in State
policy account for a significant percentage of the decline in
recipiency.
Corson and Nicholson found that between 21 percent and
55 percent of the decline in the number of recipients is attribMonthly Labor Review
September 1995
35
Unemployment Benefits
utable to State policy changes. Specifically, the decline is
due to:
• 9 to 11 percent to increases in denial rates for disquali
fying income;
• 3 to 11 percent to increases in the minimum earnings
required to qualify for ui;
• 2 to 11 percent to increases in the denial rate for mis
conduct;
• up to 13 percent to changes in voluntary separation stan
dards;
• 5 percent to reductions in maximum duration of ben
efits;
• 2 to 4 percent to changes in wage replacement rates.18
Corson and Nicholson also found that the ratio of ui claim
ants to the total number of unemployed would have increased
between 1 percent and 13 percent as the result of reductions
in work test denials, partially canceling the effects of the other
factors.19
Burtless and Saks also concluded that State legislative and
administrative changes are the primary cause of the decline
in rates of change in the number of recipients, but they did
not present estimates of the magnitude of the effects of these
changes.20
Marc Baldwin and Richard McHugh suggested that State
policy changes account for 54 percent of the 1979-90 decline
in recipiency.21 An updated work by Baldwin, however, found
sharp reductions in the apparent effects of State policy
changes.22 Baldwin and McHugh attributed the decline to:
• 21 p ercent to in crea ses in the m in im u m earnings re
quired to qualify for UI;
• 16 percent to increases in the earnings required to qualify
for the maximum benefit;
• 8 percent to increases in the number of States with dis
qualification periods for job quitters;
• 7 percent to increases in the number of States with dis
qualification periods for refusal of suitable work;
• 1 percent to increases in the number of States withrightto-work laws.23
But Rebecca Blank and David Card found little evidence
that State policy changes had any impact on recipiency. They
found that individual eligibility for ui benefits appeared to
decline slightly as the result of tighter State eligibility stan
dards, although these effects were offset by increasing wage
levels.24
Population shifts. An increasing share of U.S. unemploy
ment is in Southern and Mountain states, where the ratio of
UI claimants to the total number of unemployed has consis
tently been lower than the national average. As the percent
age of national unemployment in these States increases, the
36
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Federal Reserve Bank of St. Louis
September 1995
national ratio of ui claimants to the total number of unem
ployed would be expected to fall accordingly. This is a long
term demographic trend, occurring throughout the last three
decades and continuing into the present. Blank and Card
found that these regional shifts in population accounted for
approximately 50 percent of the decline in the national ratio
of UI claimants to the total number of unemployed between
1977 and 1987.25 Wayne Vroman asserted that 25 percent is
a more appropriate figure,26 and Corson and Nicholson at
tributed 16 percent of the variation to geographic population
shifts.27
However, these analyses do not explain the underlying
variations in ratio of UI claimants to the total number of un
employed across States that have caused the national rate to
be affected by interstate migrations. Much of this variation
can likely be attributed to differences in State policy, although
the exact extent to which this is the case has not yet been
determined.
Decline in unionization. Between 1979 and 1988, the per
centage of unionized employees decreased 25 percent.28 Be
cause unions have traditionally represented a powerful source
Table 2.
Percent of total unemployed who are unemploy
ment insurance claimants, by State 1993
State
Percent
Alaska..........................
Hawaii..........................
Vermont.......................
District of Columbia.....
Connecticut.................
Washington..................
Oregon.........................
Idaho............................
Pennsylvania...............
Wisconsin....................
Rhode Island...............
Montana.......................
New Jersey.................
Arkansas.....................
Massachusetts............
Iowa.............................
Nebraska.....................
California......................
New York.....................
Tennessee ...................
Puerto Rico..................
Delaware.....................
Nevada ........................
Illinois...........................
Kansas.........................
Minnesota....................
63.6
53.1
53.1
45.3
45.0
44.4
43.3
40.5
39.9
39.8
39.7
38.9
38.7
37.6
36.5
36.4
35.8
34.6
34.5
33.7
33.0
32.1
32.0
31.8
31.8
31.6
State
Florida...................
North Dakota.........
Michigan................
Missouri.................
Colorado................
Wyoming...............
Arizona..................
Mississippi.............
Kentucky...............
Maryland...............
North Carolina.......
Utah.......................
Maine.....................
South Carolina......
Ohio.......................
West Virginia.........
Alabama................
Louisiana...............
Texas.....................
Georgia.................
Oklahoma..............
New Mexico...........
Indiana...................
New Hampshire....
Virginia...................
South Dakota........
N ote : Data for the Virgin Islands are not available.
S ource: U.S. Department of Labor (1994).
Percent
30.1
30.0
29.8
29.4
28.5
28.5
28.3
27.7
27.5
27.5
27.2
27.0
26.2
25.4
24.9
23.5
22.5
21.8
21.4
21.3
21.1
20.7
20.6
20.3
17.0
15.3
Chart 4.
Proportion of job losers who are Ul claimants, 1970-93
Percent
Percent
-
100
-
90
-
80
40 -
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
NOTE: Shaded regions denote recession from peak to trough.
SOURCE: Council of Economic Advisers (1994).
Chart 5.
Recipiency rate for regular State unemployment insurance programs and total unemployment rate,
in percent, 1950-93
Ratio of Ul claimants
to total unemployment
Total
unemployment rate
35
30
NOTE: Shaded regions denote recession from peak to trough.
SOURCES: Council of Economic Advisers (1994) and U.S. Department of Labor (1994).
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
Monthly Labor
Review
September
1995
37
Unemployment Benefits
of information regarding available benefits for unemployed
workers, the decline in union membership could have exac
erbated problems related to distributing information among
the unemployed. In addition, unions have often helped mem
bers file Ul claims by guiding them through the U l system.
Finally, many union members are eligible only for supple
mental unemployment benefits paid by their union if they
apply for regular ui.
Blank and Card attributed 25 percent of the decline in
recipiency to the decline in unionization.29 Baldwin and
McHugh assigned 29 percent of the drop in recipiency to the
decline in unionization.30 Vroman also points to the potential
importance of the unions’ information role by noting that the
most important reason for nonapplication for Ul benefits by
unemployed individuals is their belief that they are ineligible
for ui.31 Inability to understand eligibility conditions may
cause eligible workers to fail to apply.
Decline in the manufacturing sector. As noted above,
Burtless and Saks suggested that industrial shifts contributed
to the long-term decline in recipiency. This trend continued
in the 1980’s as manufacturing as a percentage of total em
ployment fell by 22 percent between 1979 and 1990. This
factor also has been identified as a significant cause of the
short-term decline. Corson and Nicholson found that between
4 percent and 18 percent of the decrease in the ui claims ratio
can be attributed to the decline in the manufacturing sector.32
Baldwin and McHugh attributed 16 percent of the total de
cline in the ratio of U l claimants to the total number of unem
ployed to this factor.33
In addition, Corson and Nicholson noted that an unem
ployed worker who had been employed in manufacturing is
25 percent more likely to collect ui than a similar worker from
another industry. These findings are partially called into ques
tion, however, in analyses by Corson and Anu Rangarajan,34
and Baldwin.35 They found that a decline in manufacturing
employment leads to an increase in the insured unemploy
ment rate. Overall, it should be noted that because unions
traditionally have been composed disproportionately of work
ers in the manufacturing sector, the decline in manufacturing
is closely linked to the decline in unionization. As a result,
the effects of the factors may be difficult to separate.
I n s u m , the percentage of the unemployed who receive Un
employment Insurance benefits has declined steadily, with a
particularly sharp decline in the early 1980’s. This suggests
that the relevance of the system to the needs of today’s work
force has been eroded. A number of factors have contributed
to this erosion, including Federal and State policy changes,
broad demographic changes, and the decline in the manufac
turing sector and in unionization. The resulting decline in
recipiency has jeopardized the program’s capacity to carry
out its two primary functions: wage replacement for involun
tarily unemployed individuals and the countercyclical stabi
lization of the economy.
□
Footnotes
1 Employees also pay ui taxes in Alaska, New Jersey, Pennsylvania, and West
Virginia. In some o f the four States, payment by employees depends on the
status o f the ui trust fund.
2 State and local governments and many nonprofit organizations do not pay ui
taxes. They reimburse the ui system directly for benefits paid to their former
employees.
3 Rebecca M. Blank and David E. Card, “Recent Trends in Insured and Un
insured Unemployment: Is There an Explanation?” Q u a r te r ly J o u r n a l o f E c o
n o m ics, November, 1991.
Marc Baldwin and Richard McHugh, “Unprepared for Recession: the Ero
sion o f State Unemployment Insurance Coverage Fostered by Public Policy in
the 1980s,” Economic Policy Institute Briefing Paper, February 1992, also find
results that are consistent with this conclusion.
4 Data produced by U.S. Department of Labor, Unemployment Insurance
Service, Division of Actuarial Services.
5 In nine States, all eligible claimants have uniform potential durations.
6 Massachusetts and Washington allow benefits for up to 30 weeks.
7 The insured unemployment rate is defined as the number of regular ui ben
efit claimants divided by the average number of employees covered by ui over 4
o f the last 6 completed calendar quarters. The total unemployment rate is de
fined as the number o f all active unemployed job seekers divided by the total
civilian labor force.
8 The specific measure of recipiency used by researchers in examining this
question has varied. Walter Corson and Walter Nicholson, A n E x a m in a tio n o f
D e c lin in g u i C la im s D u r in g th e 1 9 8 0 s, Unemployment Insurance Occasional
Paper 88-3 (U.S. Department of Labor, 1988) examined both ratios, but fo
cused upon the ratio o f ui claimants to the total number of unemployed, which
they call the ui claims ratio.
38
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September 1995
Blank and Card, in “Recent Trends,” also examined this measure, which they
call the fraction o f insured unemployment.
Wayne Vroman, Th e D e c lin e in U n e m p lo y m e n t I n su ra n ce C la im s A c tiv ity
in th e 1 9 8 0 s, Unemployment Insurance Occasional Paper 91-2, (U.S. Depart
ment of Labor, 1991) also focused on the ratio ofui claimants to the total num
ber of unemployed.
Baldwin and McHugh, “Unprepared for Recession,” also examine the ratio of
ui claimants to the total number of unemployed, but include Extended Benefits
recipients in addition to regular State ui recipients.
9 “The Uncompensated Unemployed: An Analysis o f Unemployed Workers
Who Do Not Receive Unemployment Compensation,” Congressional Research
Service, 1990.
10 The ratio of the insured unemployment rate to the total unemployment rate
and the ratio o f ui claimants to the total number of unemployed can be statisti
cally predicted quite accurately for the years up to 1980 by knowing two vari
ables: the year, which reflects the long-term decline of the system, and the unem
ployment rate, because the ratio tends to increase significantly during periods o f
high unemployment. Since 1980, however, the recipiency ratios no longer have
the same statistical relationship to these two variables.
11 Gary Burtless and Daniel Saks, “The Decline in Insured Unemployment
During the 1980s,” Unpublished Brookings Institution Report to the Depart
ment of Labor, March 1984, p. 42.
12 Burtless and Saks, “The Decline in Insured Unemployment During the
1980s,” p. 20.
13 This particularly was likely to be true for State and local government em
ployees because they experienced low levels of unemployment in the early 1980’s.
14 Burtless and Saks, “The Decline in Insured Unemployment,” p. 17.
15 Ib id ., p. 19-20.
16 U n e m p lo y m e n t In su ra n ce: P r o g r a m ’s A b ility to M e e t O b je c tiv e s J e o p
a r d iz e d (Washington, d c , U.S. General Accounting Office, 1993), pp. 30-37.
17 Corson and Nicholson, A n E x a m in a tio n o f D e c lin in g u i C la im s , pp.
119-20.
18 Any apparent discrepancy in totals is due to rounding.
19 Corson and Nicholson, A n E x a m in a tio n o f D e c lin in g u i C la im s , pp.
119-20.
20 Burtless and Saks “The Decline in Insured Unemployment,” 1984, pp.
54-80.
21 To facilitate greater comparability between the findings of Baldwin and
McHugh, “Unprepared for Recession,” and those of other studies, Baldwin and
McHugh’s findings have been reformulated in the text. In particular, they report
that State policy changes account for 97.4 percent of the total net change in ratio
o f ui claimants to the total number o f unemployed, rather than 54 percent re
ported in the text. Overall, they find three primary factors that contributed to the
decline in the ratio o f ui claimants to the total number of unemployed and other
factors that partially offset the decrease. As a result, when only the three factors
that decrease the ratio are combined, they are larger than the net decline. Each
o f the factors independently appears to be a large percentage of the net decrease.
To determine the relative impact o f each factor, the percentage of the overall
negative impact upon the ratio of ui claimants to the total number of unem
ployed that is attributable to each o f those factors that decreases in the ratio of ui
claimants to the total number o f unemployed must be calculated. These calcu
lations indicate that State policy changes account for 54 percent of the decrease
in the ratio o f ui claimants to the total number of unemployed, declining union
ization for 29 percent, and decreases in the manufacturing sector for 16 percent.
The remaining 1 percent is attributable to the lagged unemployment level.
22 The research literature has not yet reconciled the variations in the results
found by Marc Baldwin, “Benefit Recipiency Rates Under the Federal/State
Unemployment Insurance Program: Explaining and Reversing Decline,” Un
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
p u b lish e d P h .D . d is s., M a ssa ch u setts Institu te o f T ec h n o lo g y , 1 9 9 3 ),and by
B a ld w in and M c H u g h , “U np repared fo r R e c e s s io n ,” 1 9 9 2 , p. 18.
23 A n y apparent d iscre p a n cy in to ta ls is d u e to ro u n din g.
24 B lan k and Card, “R ecen t Trends in Insured and U ninsu red U n em p lo y m en t,”
p. 1166.
25 Ib id ., p. 1 177.
26 V rom an, Th e D e c lin e in U n e m p lo y m e n t In su ra n ce, p. 13.
27 B u rtless d is m is se d reg io n a l sh ifts as a p o ss ib le ex p la n a tio n . H o w ev er, later
stu d ies h a v e ap peared to co n fir m th e m erit o f th is factor. “W h y is Insured U n
em p lo y m e n t S o L o w ? ” B ro o k in g s P a p e r s on E c o n o m ic A c tiv ity (W ash in gton ,
B ro o k in g s In stitu tion , 1 9 8 3 ), pp. 2 2 5 - 4 9 .
dc,
28 M ich a el A . C urm e, et al. “U n io n M em b ersh ip and C ontract C o v era g e in the
U n ited S ta tes, 1 9 8 3 - 1 9 8 8 ,” I n d u s tr ia l a n d L a b o r R e la tio n s R e v ie w , O cto b er
1 9 9 0 , pp. 5 - 3 4 , and E d w ard C . K o k k ele n b er g and D o n n a R. S o c k e ll, “U n io n
M em b ersh ip in th e U n ited S tates, 1 9 7 3 - 1 9 8 1 ,” I n d u s tria l a n d L a b o r R e la
tio n s R e v ie w , Ju ly 1 9 8 5 , pp. 4 9 7 - 5 4 2 .
29 B lan k and Card, “R ecen t Trends in Insured and U ninsu red U n em p lo y m en t,”
p. 1179.
30 B a ld w in and M c H u g h , “U np repared fo r R e c e s s io n ,” p. 18.
31 V rom an, The D e c lin e in U n e m p lo y m e n t In su ra n ce, p. 2 5 .
32 C o rso n and N ic h o ls o n , A n E x a m in a tio n o f D e c lin in g u i C la im s, pp.
1 1 9 -2 0 .
33 B a ld w in and M c H u g h , “U np repared fo r R e c e s s io n ,” p. 18.
34 W alter C o rso n and A n u R angarajan, “E x ten d ed u i B e n e fit T rig g ers,”
(P rin ceto n , n j , M a th em a tica P o lic y R esea rch , 1 9 9 3 , em p h a size that this resu lt is
u n e x p e cted , and s u g g e st that it sh o u ld b e v ie w e d w ith ca u tio n .
35 B a ld w in , “ B e n e fit R e c ip ie n c y R a tes,” p. 2 0 1 .
Monthly Labor Review
September 1995
39
Comparing measures
of educational
attainment in the CPS
Harley Frazis,
Michelle Harrison Ports,
and Jay Stewart
ducational attainment is an im
portant demographic variable
about which information is col
lected in household surveys such as the
Current Population Survey ( c p s ). How
ever, survey measures of education, like
measures of other population character
istics, are imperfect. Educational at
tainment can be an ambiguous concept.
At the elementary and high school lev
els of education, it is relatively clear
what is meant by a grade or year of
schooling. But the distinction is less
clear at postsecondary levels: a “year”
may represent the amount of time spent
in schooling, or it may represent a cer
tain amount of progress toward a de
gree.
College degrees and high school di
plom as are key elem ents in m ost
people’s perceptions of educational at
tainment, but until 1992, the attainment
of a degree was not explicitly part of
the education measure used in the c p s .
In January of that year, the cps intro
duced a new education item consisting
of a single question: “What is the high
est level of school. . . has completed or
the highest degree . . . has received?”1
The old item (prior to January 1992)
asked respondents two questions: (1)
“What is the highest grade or year of
regular school . . . has ever attended?”
and (2) “Did . . . complete the grade?”
While the old item did not explic
itly ask about the attainment of a de-
E
Harley Frazis and Jay Stewart are econo
mists in the Office of Employment Research
and Program Development, Bureau of
Labor Statistics. Michelle Harrison Ports is
an economist formerly in the Division of
Data Development, Bureau of Labor Sta
tistics.
40
Monthly Labor Review
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Federal Reserve Bank of St. Louis
gree, the interview er’s instructions
made it clear that certain levels of edu
cation carried the connotation of a de
gree. For example, people who passed
a high school equivalency test or who
completed high school in the Armed
Forces were supposed to be coded as
having completed the 12th grade, re
gardless of the highest grade they actu
ally completed. Similarly, for college,
c p s interviewers were instructed that
“school years are determined by the
number of credits required for complet
ing . . . a degree.”2However, interview
ers were not instructed to probe for high
school diplomas and college degrees,
which means that these credentials were
probably not picked up in many cases
when respondents took less than 4 years
to finish high school or college.
Before the new item was introduced,
it was field tested by the Census Bu
reau in February 1990. All respondents
were asked the three questions ,consti
tuting the new and the old items. To
minimize the number of people who
relied on their response to the old item,
the new item was placed at the end of
the survey, while the old item was asked
at the beginning of the survey, as usual.
These data present a unique opportunity
to examine the information elicited by
each question.
This article compares the responses on
the two education items in order to shed
light on how successfully educational at
tainment is measured by each item. A
finding which emerges is that the old item
led to more consistent measurement of
precollege-level educational attainment,
probably due to the distinction made be
tween attending and completing a grade.
However, use of the old item leads to a
substantial number of errors in attribut
ing degrees to individuals.
The basic tool used in investigating
this issue is the examination of conflict
ing responses. Two different levels of
conflicting responses are distinguished:
inconsistent responses and classification
errors. A pair of responses to the new
and old items is inconsistent if it is im
September
1995
possible for both responses to be cor
rect; a classification error occurs if the
answer to the old item is not consistent
with the degree-based intent of the old
item. As an example of the latter, con
sider a person who responded to the old
item that she completed ninth grade, but
also responded to the new item that she
has a general equivalency diploma
( g e d ). This response pattern conflicts
with the degree-based intent of the old
question, even though the responses are
consistent as the term is defined above.
Note that the classification scheme
is hierarchical: all inconsistent re
sponses are classification errors, but not
all classification errors are inconsistent
responses. Throughout the article, the
term conflicting responses is used when
it is not necessary to distinguish between
inconsistent responses and classification
errors.
When responses are consistent, the
intent of the old question (to make the
completion of certain grades equivalent
to specific degrees) is used as a crite
rion for determining whether a pair of
responses is a classification error. For
example, if the responses to the old and
new items were “ 12th grade, com
pleted” and “ 12th grade, no diploma,”
this would be a classification error.
A ssociate’s degrees are treated as
equivalent to 2 years of college, so that
cases with associate’s degrees but fewer
than 14 years of school completed are
classification errors. Similarly, because
4 years of college are supposed to be
equivalent to a bachelor’s degree, cases
with bachelor’s degrees and fewer than
16 years of school completed are clas
sification errors, as are those with
associate’s degrees or “some college, no
degree” and 16 or more years of school.
At the postgraduate level, things be
come som ewhat more am biguous.
Those with fewer than 17 years of
school completed and possessed of
master’s degrees, as well as those with
fewer than 18 years completed and hold
ing professional or doctoral degrees, are
also classification errors.3
I
Rates of inconsistent responses a n d classification errors in
responses to th e e d u c a tio n item s, b y response to o ld item
[Percent]
Years of
school
completed
Inconsistent
responses
Classification
errors
Total..........................................................
6.1
9.6
Elementary:
0 ................................................................
1 ................................................................
2 ................................................................
3 ................................................................
4 ................................................................
5 .................................................................
6 ................................................................
7 .................................................................
8 .................................................................
6.3
16.2
6.1
3.9
12.1
3.5
3.3
2.9
8.0
6.3
17.7
12.4
3.9
12.3
3.7
4.6
3.6
9.5
. High school:
1 ................................................................
2 .................................................................
3 ................................................................
4 ................................................................
17.8
14.9
4.5
7.2
19.4
17.1
12.0
10.2
6.3
4.2
2.6
.9
.2
.2
10.4
4.2
7.7
9.5
7.3
1.6
College:
1 ................................................................
2 ................................................................
3 ................................................................
4 ................................................................
5 ...................................................................
6 or more.......................................................
|
R a te s o f in c o n s is t e n t r e s p o n s e s a n d c la s s if ic a t io n e r ro rs in
r e s p o n s e s t o t h e e d u c a t i o n ite m s , b y r e s p o n s e t o n e w it e m
[Percent]
H igh est g r a d e
c o m p le te d or
d e g r e e r e c e iv e d
T o tal..................................................................
In con sistent
resp onses
C las sific atio n
errors
6.1
9.6
No school............................................................
Nursery school......................................................
Kindergarten...............................................
5.1
5.1
—
-
First through fourth grade..................................
Fifth through eighth grade.....................................
Ninth grade.......................................................
Tenth grade..............................................................
Eleventh grad e........................................................
Twelfth grade, no diploma......................................
Twelfth grade, with diploma or
graduate equivalency degree.............................
6.2
3.9
13.0
14.6
18.0
6.5
4.8
6.8
Some college, no degree.......................................
Associate's degree:
Occupational........................................................
Academic............................................................
Bachelor's degree..............................................
Master's degree............................................
Professional degree............................................
Doctoral degree................................................
6.8
9.3
8.7
2.3
1.7
.5
10.3
.6
26.9
18.4
3.0
5.2
13.2
1.8
No t e : Dashes indicate fewer than 10 observations.
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_
_
6.2
3.9
13.0
14.6
18.0
62.9
Conflicts by edu catio n
Tables 1 and 2 indicate that conflicting
responses are more common at some edu
cation levels than others. In particular,
inconsistent responses occur primarily at
grade levels that are at the low or high
end of the new categories. For example,
inconsistency rates are higher than aver
age for people with 1, 4, and 8 years of
education. Inconsistency rates also are
higher than average for people with 9 and
10 years of education. In all these cases,
the discrepancy arises because, when an
swering the new question, many people
did not make the distinction between the
highest grade they attended and the high
est grade they completed.
Most of the conflicting responses for
people who have completed 9 to 12
years of schooling are due to a particu
lar response pattern. In that pattern, the
person responded to the old question
that he or she attended, but did not com
plete, for instance, 10th grade. When
asked the new question, the person re
sponded “10th grade.” This is not con
sistent because the new question asks
for the highest grade completed. Such
a response pattern accounts for 2.1 per
cent of all responses, which is more than
one-third of all inconsistent responses.
Why are the high school years confus
ing? The inconsistent response pattern
just described has two possible expla
nations: (1) Individuals may have re
membered their response to the old
question and simply repeated that re
sponse. For example, an individual who
responded that he attended, but did not
complete, ninth grade may again have
responded, unthinkingly, “ninth grade”
to the new question. (2) Respondents
may not be very careful in making the
“attended-completed” distinction unless
they are specifically asked questions that
would lead them to do so.
Using the February 1990 data alone,
one cannot determine which of these
hypotheses is correct. To do this re
quires data sets that contain responses
Monthly Labor Review
September
1995
41
Technical Note
to the two education items from two January 1992 matched data contradicts 3.0 percent in the January-February
different interviews. In that case, the hypothesis (1), but supports hypothesis matched data.
respondent is not likely to have remem (2). The “attended-completed” incon
bered the response to the first question sistency occurs more frequently in the C orrespondence betw een years o f
matched data. If hypothesis (1) were schooling and highest degree attained.
in answering the second question.
To shed light on which of the two correct, then one would expect that the A major reason for changing the edu
hypotheses is correct, data from De “attended-com pleted” inconsistency cation item was that it is difficult to
cember 1991 were matched with data would occur less frequently in the infer whether a person holds a degree
from January 1992.4 The matched data matched data because the answer to the from the number of years of schooling
set, like the data of February 1990, con new item could not have been affected the person has. The new item represents
tains both the new and old education by the answer to the old item. It ap a significant improvement in that it is
items (the old item from December pears that having answered the old item now possible to identify six types of
1991, the new item from January 1992). helped respondents answer the new college degree (two types of associate’s
As noted earlier, the key difference be item in the February 1990 data. degree, in addition to the bachelor’s,
tween the two is that the questions were Matched January 1990-February 1990 master’s, professional, and doctoral de
not asked during the same interview in data, which contain two independent grees), as well as high school diplomas.
the matched data set. If the inconsis measures using the old item, also sup A b ls news release explains the ration
tencies noted above appear in the port hypothesis (2): respondents do ale for the change:6
matched sample, then, clearly, the re make a careful distinction between
The years-of-school-completed
concept had been used to measure
spondents did not hear the word “com completing a grade'and merely attend
educational attainment in the Current
pleted” in the new item. The absence ing a grade when specifically asked
Population Survey since 1948 and,
of these inconsistencies in the matched questions that would lead them to do
until recently, was considered ad
data would indicate that the response so. For people with 9 to 11 years of
equate for this purpose. Persons who
to the old question affected the response schooling, error rates5were between 9.3
reported that they had attended high
school for 4 years, for example, could
percent and 11.9 percent in the Febru
to the new question.
reasonably be considered high school
Evidence from the December 1991- ary 1990 data, but only 2.5 percent to
Correspondence between number of years of schooling and highest degree held Ì
high school and college graduates
Percent of p e o p le with—
Age,
years
Total...........................................................
16 1 9 ..............................................................
20 24 ..............................................................
25 29 ..............................................................
30 34 ..............................................................
35 39 ..............................................................
4 0 -4 4 ..............................................................
45-49 ..............................................................
50 54 ..............................................................
55 59 ..............................................................
60-64 ..............................................................
65-69 ..............................................................
70 74 ..............................................................
75 and older....................................................
12 years of
schooling
w ho h ave a
high school
dip lom a,
but no
c o lle g e
16 years of
schooling
w ho h a v e a
bachelor's
d e g re e ,
but no
postgraduate
d e g re e
12 or m ore
years of
schooling
w ho h a v e a
high school
d ip lo m a
85.1
90.2
97.9
94.4
97.1
97.9
98.0
98.3
98.4
98.5
98.4
97.8
97.3
97.5
97.2
97.1
95.9
91.2
93.6
94.4
94.9
95.1
94.9
94.5
94.8
95.5
95.2
93.4
93.8
62.3
80.9
85.2
86.5
86.1
85.9
86.7
88.3
88.2
89.1
89.5
88.1
85.7
N ote: Dashes indicate category is not applicable.
42
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Federal Reserve Bank of St. Louis
September
1995
—
90.8
91.9
91.3
90.4
89.6
87.6
88.6
89.9
91.3
89.9
88.3
88.2
16 or m ore
years of
schooling
w ho h a v e a
b a c h e lo r’s
d e g re e
graduates; those with 4 or more years
of college could be considered col
lege graduates. Prior to 1970, the
number of years of schooling did, in
deed, correspond quite well with the
attainment of certain degrees (in the
manner noted above). Several stud
ies conducted by the Bureau of the
Census over the last several years,
however, indicated that this relation
ship had weakened. That is, many
people who said they had a particu
lar number of years of schooling had*
not in fact received the degree typi
cally associated with that level of
schooling.
Much of the increased discrepancy be
tween administrative and survey esti
mates of the stock of college graduates
can be attributed to increases in the num
ber of people who have attended college.
However, it is less clear that there is an
increased discrepancy in terms of percent
ages. For example, administrative data
from the decade 1940-50 underestimate
the 1950 stock of those with 16 or more
years of education by 419 thousand,
which is 7.2 percent of the total of 5.8
million; 1970-80 administrative data un
derestimate the 1980 stock by 1,659,000,
which is 7.0 percent of the total of 23.5
million.7
Although the old item attempted to
identify the degrees earned to the full
est extent possible, it had no way of
dealing with people who completed 12
or 16 years of schooling but did not have
high school diplomas or bachelor’s de
grees. Table 3 examines the correspond
ence between the number of years of
education a person has and the degree
conferred on that person for both high
school and college graduates, and
whether the relationship has weakened
over time. The findings support the no
tion that it is difficult to infer whether a
person holds a degree from the number
of years of schooling the person has, but
the extent of misclassification depends
on the way in which the degree catego
ries are defined. However, the Febru
ary 1990 data do not support the con
tention that the relationship between the
two variables has weakened over time.
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When the Census Bureau and the Bu
reau of Labor Statistics tabulate statis
tics by educational attainment, it is gen
erally assumed that people who have
completed exactly 12 years of school
ing have a high school diploma and no
college, and that people who have com
pleted exactly 16 years of schooling
have a bachelor’s degree and no gradu
ate education. The first two columns
of the table show the extent to which
this assumption is accurate: only 85.1
percent of people with exactly 12 years
of schooling have a high school diploma
(and no college), which means that
nearly 15 percent of these people are
misclassified. This suggests that the
number of years of schooling is not a
good way of identifying people who
stop their education with a high school
diploma. The correspondence for
people with exactly 16 years of school
ing is somewhat better, but still quite
imperfect: only 90.2 percent have a
bachelor’s degree (and no graduate edu
cation).
It is worth noting that the number of
years of schooling refers to completed
years. Hence, people who completed
less than a year of college or less than
Table 4.
a year of graduate school are counted as
having exactly 12 and 16 years of school
ing, respectively. The correspondence
between these two classifications im
proves when the definition excludes
people who attended, but did not com
plete, the next grade. For people with 12
years of schooling, the correspondence
increases to 91.6 percent; for people with
16 years of schooling, it increases only
slightly, to 90.7 percent.
While people with 13 or more years
of school are virtually certain to have a
high school diploma, many with more
than 16 years of school do not have a
bachelor’s degree. Nearly 98 percent
of people with 12 or more years of
schooling have a high school diploma,
while 94.4 percent of people with 16
or more years of schooling have a
bachelor’s degree.
One can infer whether the relationship
between the number of years of school
ing and holding either a high school
diploma or a bachelor’s degree has
changed over time by looking at these
percentages for different cohorts. If the
correspondence has been deteriorating
over time, then it should be greater for
older cohorts. From table 3, however,
Rates of inconsistent responses and classification errors
in responses to education items, by type of respondent
and month-in-sample
[Percent]
C a teg o ry
Total................................................
Inconsistent
responses
Classification
errors
6.1
9.6
Type of respondent:
Self.,........................................
Proxy.............................................
Self and proxy..............................
5.6
6.6
6.2
9.3
10.0
9.2
Month-in-sample:
11.......................................
2 ...................................................
3 ......................................................
4 ..............................................
51...............................
6 .................................................
7 ..................................................
8 ...................................................
4.1
6.0
6.5
6.7
5.0
7.0
6.5
7.1
6.9
9.6
9.8
10.5
8.1
10.5
10.2
11.0*
11nterviews in these months are more likely to be in person. The vast majority of interviews during
months-in-sample 2-4 and 6-8 are conducted over the telephone.
Monthly Labor Review
September
1995
43
Technical Note
this does not appear to be true. For
people with 12 or more years of school
ing, the correspondence is fairly con
stant across cohorts. For people with
exactly 12 years of schooling, the cor
respondence is low for 16- to 19- and
20- to 24-year-olds. Between the ages
of 25 and 50 years, the correspondence
is relatively constant at 85 percent to
86 percent. There is a slight increase,
to about 88 percent, at age 50. For
people with 16 years and 16 or more
years of schooling, there is not much
difference by cohort.
Other survey issues
As noted previously, responses to the
new item at the time of the test may
have been affected by the response to
the old item; that is, the order of the
questions in the survey may have af
fected the outcome. Two other aspects
of the survey instrument that could af
fect consistency rates also were exam
ined: whether the response was self-re
ported or by proxy and the individual’s
month-in-sample.8 (See table 4.)
As expected, self-respondents are
less likely than proxies to give conflict
ing responses, but the difference is not
large. When the respondent type is self
and proxy (that is, both provided infor
mation), the percentage of classification
errors is very close to that of self-re-
spondents, while the percentage of in
consistent responses is between that for
self- and proxy respondents.
With regard to rotation group, in
coming rotations (months-in-sample 1
and 5) give fewer conflicting responses.
The most likely explanation is that in
terviews in these months are conducted
in person. Interviews in the other 6
months are conducted predominantly by
telephone. This is an important distinc
tion because, in responding to questions
posed in the new item, respondents are
shown flashcards with the possible re
sponses when the interview is in per
son, whereas if the interview is by tele
phone, the possible responses are read
only if the respondent is unsure.
I n t h i s a r t i c l e , data collected in Feb
ruary 1990 were used to examine con
flicting responses in reporting educa
tional attainment in the c p s in order to
shed light on how well educational at
tainment is measured by the old and
new questions. Results of the study
show that consistency rates vary by edu
cation level. Some of the variation is
due to respondents failing to make the
distinction between having completed
a grade and merely attending school
during that grade. It appears that pre
senting the old education item before
the new one (as was done in February
1990) helps respondents make the dis
tinction more readily. On the other
hand, much of the inconsistency in re
sponses is due to the old question not
picking up information about the de
grees the respondents have or have not
earned. Other aspects of the survey in
strument also have an effect on the rate
of conflicting responses: face-to-face
interviews produce fewer conflicting
responses than do telephone interviews,
and proxy respondents are slightly more
likely than self-respondents to give con
flicting responses.
The current education item in the c p s
represents a completely different way
to measure educational attainment than
the old item did. The current measure
provides detailed information about
educational credentials that was unob
tainable under the old measure, al
though some precision has been lost at
both the college and lower levels.
In c p s surveys starting in January
1996, the Census Bureau and the Bu
reau of Labor Statistics plan to expand
the level of detail available in the col
lege range and to distinguish between
regular high school diplomas and g e d ’ s .
The 1996 item will ask the current ques
tion first. Then, depending on the an
swer, follow-up questions may gather
more detail on the respondent’s educa
tional attainment. This should further
improve the measurement of education
in the c p s .
□
Footnotes___________________
1The new item is discussed in Robert Kominski
and Paul M. Siegel, “Measuring education in the
Current Population Survey,” M o n th ly L a b o r R e
v ie w , September 1993, pp. 34-38.
2c p s I n te rv ie w e r s M a n u a l
(Bureau of the Cen
sus, February 1987).
3 Note that the absence of a category designat
ing some graduate school, but no graduate degree,
precludes those with more than 16 years of school
completed and holding a bachelor’s degree from
having their responses classified as inconsistent.
4 The 4-8^1 rotation scheme in the c p s makes it
possible to match individuals in consecutive
months. A household is interviewed each month
for 4 consecutive months, is out o f the survey for 8
months, and then is back in the survey for 4 months.
Households are identified by th eir m o n th -in -sa m p le,
which ranges from 1 to 8. In any given month, it is
44
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Federal Reserve Bank of St. Louis
responses that fit this pattern, resulting in an in
consistency rate o f 11.9 percent. In the JanuaryFebruary matched data, the analogous population
is those who responded that they attended 11th
5 In the February 1990 data, an observation was grade both times that the old item was asked. Of
considered an error if respondents did not make
these people, 2.8 percent gave different answers
the “attended-completed” distinction. To illus
to the “attended-completed” questions.
trate, consider people who reported having at
6 E d u c a tio n a l A tta in m e n t o f A m e ric a n W orkers:
tended 11th grade when asked the old item and
S o m e N e w D a ta , u s d l 93-238 (Bureau o f Labor
responded “ 11th grade” to the new item. The
Statistics, Jul. 16, 1993).
responses are consistent if (1) the person re
possible to match the responses o f individuals
whose month-in-sample is 2 through 4 or 6 through
8 with their responses in the previous month.
sponded “ 11th grade” and “did not complete” to
the old item and “ 10th grade” to the new item; or
(2) the person responded “11th grade” and “com
pleted” to the old item and “11th grade” to the
new item. O f all the pairs of responses, 2,663 fit
(1) and 2,117 fit (2). A pair o f responses is in
consistent if the person responded “ 11th grade”
and “did not complete” to the old item and “11th
grade” to the new item. There were 647 pairs of
September
1995
7The numbers are taken from R. Kominski and
R M. Siegel, “Measuring Educational Attainment
in the 1990 Census,” paper presented at the annual
meeting o f the American Sociological Association,
August 1987. The 1960 and 1970 discrepancies
are lower.
8 See footnote 4 for an explanation of m o n th -in sa m p le .
Strike averted at
a t &t
Negotiators for the American Tele
phone & Telegraph Co. (AT&T) and its
two major unions— the Communica
tions Workers of America (CWA) and the
International Brotherhood of Electri
cal Workers (IBEW)—averted a threat
ened strike when they reached tentative
agreement on new 3-year master con
tracts covering some 110,000 workers
nationwide. Terms of the pacts, which
are similar to those negotiated by the
unions with n y n e x last year, are ex
pected to serve as a framework for set
tlements at the regional Bell telephone
companies currently negotiating new
agreem ents w ith the unions. (See
Monthly Labor Review, January 1995,
page 35.) The major sticking points in
the at &t negotiations were the level of
wages, health care premiums for retir
ees, and union access to AT&T subsid
iaries for organizing purposes.
According to cw a president Morton
Bahr, “We made substantial improve
ment in the areas of wages, health care,
pension benefits, employment security
and training, and education for our mem
bers. We also protected the health care
of our retirees, both ensuring that they
won’t have out-of-pocket costs for pre
miums and also improving coverage.”
The contracts provide wage in
creases of 3.6 percent immediately, 3.5
percent in the second year, and 3.4 per
cent in the third year. Terms also call
for an immediate $1,000 ratification
bonus and $800 lump-sum payments in
1996, 1997, and 1998, which will be
converted into at &t stock with a share
price equal to AT&T’s average stock
price during the week of August 28,
1995. At the expiration of the prior con
tract, average wage rates ranged from
$435 per week for account representa
tives to $807 per week for equipment
installers.
"Industrial Relations" is prepared by
Michael H. Cimini and Charles J. Muhl of
the Division of Developments in LaborManagement Relations, Bureau of Labor
Statistics, and is largely based on informa
tion from secondary source.
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Federal Reserve Bank of St. Louis
The accords improve health benefits
for active workers, particularly those
enrolled in managed care plans, and
protect retirees from having to contrib
ute to health insurance premium s.
Managed care plan participants will
have 100-percent coverage for all ser
vices, including in-hospital services
and surgery, and will have newly added
coverage for routine physicals, certain
preventive care treatments, hospices,
and air ambulance services. The de
ductibles for in-network services will be
replaced by a flat $10 copayment for
doctors’ office visits, and maximum
annual out-of-pocket expenses will be
cut from $ 1,000 to $750. The settlement
also introduces improvements in the
prescription drug plan, mental health
and drug abuse program, hospice care,
and dental plan.
Employees going out-of-network for
health care will incur greater costs, in
cluding annual deductibles of $200 per
person and $400 per family, annual
maximum out-of-pocket expenses of
$2,500 per person and $5,000 per fam
ily, and a $ 150 employee copayment for
an in-hospital stay.
Retirees will be covered under the
same managed care networks, with ben
efits and copayments identical to those
of active employees. Workers who re
tired before March 1, 1990, will con
tinue to receive medical benefits fully
paid by the company. Those retiring
after March 1, 1990, will continue to
receive medical benefits without out-ofpocket costs for insurance premiums
during the term of the agreement only,
because of increased caps on AT&T’s
contributions towards premiums in
1995 and 1996 and the planned estab
lishment of a retiree Medical Spending
Account in 1997.
The settlem ent includes several
other changes in benefits. It increases
pension benefits for active employees by
12 percent over the term of the agree
ment, and boosts minimum pension
benefits for current retirees to $400 per
month. The pact obligates at &t to con
tribute $67 million over the term to
build employees’ skills. It improves the
savings and security and stock purchase
plans. Other changes in benefits amend
dependents’ group life insurance to pro
vide separate coverage for spouses and
children and increase coverage at lower
rates; continue the employee assistance
program; increase the maximum reim
bursement for adoption expenses to
$3,000 less taxes; and provide up to
$7.5 million for projects to serve em
ployees’ family needs.
In the job and union security areas,
the parties agreed to language giv
ing union members access to jobs in
AT&T units that are not unionized
and strengthening the concept of
“union values” to help nonunion work
ers to organize. They adopted a list of
“do’s” and “don’ts” for future organiz
ing campaigns at a t &t units, and
agreed to a process for organizing cam
paigns at two affiliates, at &t Transtech
and Universal Card Services. The par
ties also agreed to create a joint com
mittee to annually review issues of in
clusion or exclusion of certain at &t af
filiates for organizing purposes, the ap
plicability of card checks and the
company’s pledge of neutrality in the
unions’ organizing efforts, and the use
of joint participation models established
by other bargaining partners.
The settlement expands employees’
rights under the at &t Transfer System
plan (ATS), which originally was de
signed to provide regular full-time and
part-time employees with a vehicle to
request new career opportunities and
to provide “surplus” employees with
an increased opportunity to continue
employment with the company. New
contract language gives surplused and
laid-off workers simultaneous access
to job openings at AT&T and all its
affiliates, except McCaw Cellular. It
also gives these employees immediate
access to job opportunities when plants
are closed, instead of placing them in a
“force freeze” as was done in the past.
The Workplace of the Future (w po f )
program, which was designed to facili
tate greater union participation in hu
man resource and business planning, is
continued. The program will be the fo
cal point for addressing problems deal
ing with technological change, subcon-
Monthly Labor Review
September 1995
45
Industrial Relations
trading, and outsourcing through Busi
ness Unit Council meetings and local
negotiations.
Rule changes
featured in utility pacts
Members of Local 223 of the Utility
Workers Union narrowly ratified a new
4-year labor contract covering some
2,700 power plant workers, cable splic
ers, substation operators, and other pro
duction and maintenance employees at
Detroit Edison facilities in southeast
ern Michigan. The low approval rate
reportedly reflected rank-and-file dis
satisfaction over rule changes that give
the utility more operational flexibility,
including language making employees
exercise their seniority rights on a
multiplant basis, rather than on a plant
wide basis as stipulated under the pre
vious contract.
The pact provides wage increases of
2.5 percent in the first and third years
of the contract, and lump-sum pay
ments in the second and fourth years
equal to 2.5 percent of an employee’s
gross salary earned in the preceding 12
months. At the expiration of the prior
agreement, the average hourly base rate
reportedly was about $21.65.
The settlement introduces several
changes in benefits. The formula used
to calculate normal pensions is en
hanced to provide annual benefits equal
to 1.5 percent (was 1.4 percent) of the
average of the highest 5 years’ earnings
multiplied by the number of years of
credited service for each of the first 30
years of service and 1.4 percent of the
average of the highest 5 years’ earnings
multiplied by the number of years of
credited service over 30. The penalty
(reduction in pension benefits) for early
retirement decreases in June 1997, from
8 to 3 percent for employees retiring at
age 59, from 16 to 11 percent for those
retiring at age 58, from 24 to 19 per
cent for those retiring at age 57, from
32 to 26 percent for those retiring at
age 56, and from 40 to 35 percent for
those retiring at age 55. The supplemen
tary early retirement allowance, which
is paid to employees who retire before
46
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Federal Reserve Bank of St. Louis
reaching age 62, is increased to yield a
minimum monthly benefit, when com
bined with regular retirement benefit
total payments, of $1,250 in the first
year of the contract, $1,500 in the sec
ond year, $1,550 in the third year, and
$1,750 in the fourth year. The minimum
age requirement to qualify for such ben
efits—which are paid until the retiree
reaches age 62—drops from 56 to 55.
Other changes, all effective in 1996,
increase maximum annual orthodontic
benefits from $850 to $1,250 and am
bulance service benefits from $300 to
$400; change the employee copayment
for prescription drugs from 20 percent
of cost to $25 per prescription; and
eliminate the employee copayment for
health insurance premiums when the
employee is on long-term disability.
In another development, the Illinois
Power Company and four separate lo
cals of the International Brotherhood of
Electrical Workers (IBEW) have agreed
to separate but essentially identical 4year contracts providing early retire
ment incentives and more flexible work
rules in response to the company’s plan
to restructure its operations. The agree
ment covers some 2,600 production,
maintenance, office, and technical em
ployees working throughout Illinois—
part of the Decatur-based gas and elec
tric utility’s total work force of 4,400.
When the prior contract expired in
June 1994, the parties agreed to a 9month extension that included a 3-per
cent “premium payment” on June 30,
1994, while Illinois Power developed
its restructuring plan. Under the final
plan, several hundred unionized posi
tions will be eliminated after a number
of functions, including billing and cus
tomer service, are centralized at the
company’s headquarters.
Thus, as part of the current settle
ment, the parties negotiated early retire
ment incentives and improvements in
severance benefits intended to cushion
the effects of staff reductions. Under
changes to the early retirement pro
gram, employees will be credited with
an additional 5 years of age when cal
culating pension eligibility, enabling an
employee aged 57 or older to retire
September 1995
without penalty. Severance language is
improved to provide 3 weeks of pay for
each year of credited service, with a
minimum payment of 8 weeks and a
maximum of 52 weeks. Employees ac
cepting severance payments lose their
recall rights.
Work rule changes improve Illinois
Power’s flexibility when responding to
power outages and other emergency re
pairs, as well as conducting normal op
erations at its power plants and con
struction sites. The pact also includes
modifications to overtime policy and
emergency repair procedures to give the
utility more flexibility in redirecting its
work force.
The settlement rolls in the 3-percent
premium payment negotiated as part of
the 9-month contract extension and
provides wage increases of 3.5 percent
in the second year of the contract and 3
percent in both the third and fourth
years. In addition, employees may re
ceive annual bonuses of up to 6 percent
of earnings paid in the preceding 12
months if established corporate goals
are met.
The contract also allows employees
to take vacation in single- or half-day
increments; and precludes a strike or
lockout during the next round of nego
tiations and requires interest arbitration
in the event of a bargaining impasse.
New pact
at Kelly-Springfield
Some 1,400 production and mainte
nance workers at Kelly-Springfield Tire
Co. in Freeport, i l , will be working
under a new 3-year labor contract ne
gotiated by Local 745 of the United
Rubber Workers. Terms of the pact de
viate somewhat from those agreed to
last year by the Rubber Workers and
Goodyear Tire and Rubber Co., KellySpringfield’s parent company. (See
M onthly Labor Review, September
1994, pp. 60-61.) Unlike its Goodyear
counterpart, Local 745 agreed to lan
guage allowing management to add
continuous operations on the weekends
(two 12-hour shifts a day) and to start
new hires at rates that are below nor-
mal base rates but that reach normal
base rates over a specified period. In the
first year of the contract, work on week
ends will be on a voluntary basis; there
after, the company will have the right
to assign workers to weekend shifts.
The Kelly pact calls for a wage freeze
during the term of the contract, moder
ated by quarterly cost-of-living adjust
ments equal to 1 cent an hour for each
0.26-point change in the Consumer
Price Index for Wage Earners and Cleri
cal Workers, with 18 cents per worker
being diverted each year to help fund
the company’s performance recognition
plan. That plan establishes a target bo
nus of $1,000 per year for each em
ployee, with half coming from the com
pany and half from the c o l a diversion.
Each employee will receive a minimum
of $500 and a maximum of $1,500, with
the actual amount based in equal pro
portions on the financial performance
of Goodyear and Kelly-Springfield. Last
year, the plan payout averaged $1,375
per employee.
Other terms guarantee that the com
pany will make a capital investment of
about $17 million for radial light truck
tire production; and continue the com
pany-provided medical plan, pension
benefits, accident and sickness cover
age, supplemental workers’ compensa
tion benefits, and the vision and dental
care plans at current levels.
Farmer Jack/A&p pact
The Great Atlantic and Pacific Tea
Company and Local 876 of the United
Food and Commercial Workers reached
agreement on a 3-year contract cover
ing some 6,500 clerks at 88 Farmer Jack
and a & p grocery stores in the Detroit,
Mi, metropolitan area. According to a
prepared statement, the accord provides
“job security for employees and contin
ued growth for the company in Michi
gan.” The two chains, subsidiaries of
New Jersey-based Great Atlantic, nego
tiated a single contract covering all
unionized employees for the first time,
thus giving workers the opportunity to
move freely among stores in both
chains. With the settlement in hand,
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Federal Reserve Bank of St. Louis
Great Atlantic announced that 15 stores
originally scheduled to be closed will
remain open. In addition, the company
pledged to open 15 new stores in the
metro area over the next 2 years.
The pact provides wage increases for
top-rated employees of 25 cents per hour
on August 6, 1995, 30 cents per hour
on January 1, 1996, and 35 cents per
hour on January 1, 1997. At the expira
tion of the prior contract, the top hourly
rate was $11.82 for employees hired be
fore 1988 and $9.82 for employees hired
thereafter.
A number of work rule changes were
included in the accord. The ratio of full
time to part-time positions was reduced
from 50/50 to 30/70. In return for giv
ing Great Atlantic, this added flexibil
ity, the union received a guarantee from
the company that at least 2,000 full
time positions will remain in the bar
gaining unit during the term of the
agreement. When eligibility for depen
dent health care is determined, parttime workers will now be credited for
hours worked on Sundays and holidays,
which previously had not been included
in the computation. Employees must
average at least 34 hours of work per
week to be eligible for dependent health
care.
Other terms provide employees hired
after 1985 with 1 additional week of
vacation and 5 additional national holi
days; and maintain the current levels of
pension and health care benefits.
Hawaiian hotels settle
The Hawaii Hotel Council and Local 5
of the Hotel Employees and Restaurant
Employees settled on a 5-year master
contract that provides wage increases
and benefits improvements for some
5,000 employees. The Council bar
gained for seven hotels—the Hyatt Re
gency Waikiki, the Sheraton Princess
Kaiulani, the Sheraton Moana Surf
Rider, the Sheraton Royal Hawaiian, the
Sheraton Waikiki, the Hilton Hawaiian
Village, and the Ilikai Hotel.
The pact calls for wage increases of
around 4 percent in the first year of the
contract, and around 3 percent each in
the second and third years, with the ex
act amount dependent on an employee’s
job classification. The settlement also
includes a reopener covering wages and
health and welfare funding in 1998, and
a 6-month postponement for imple
menting “most of the money items” at
the Ilikai because of its financial diffi
culties. Under the prior agreement,
wage rates averaged $12.45 per hour
and ranged between $10 and $18 per
hour.
Besides maintaining health care ben
efits at their current levels without ad
ditional employee premium sharing, the
contract calls for several benefit im
provements. Pension benefits are in
creased by approximately $1 per month
per year of credited service in the sec
ond and third contract years, to $24 per
month in 1997, and to $25 per month
in 1998. Bereavement leave is broad
ened to cover special religious ceremo
nies for deceased family members. Em
ployees with at least 1 year of service
are eligible for up to 3 months of un
paid leave to care for newborn or
adopted newborn children—which may
be extended for an additional 3 months
by mutual agreement.
Other changes streamline grievance
and arbitration procedures, strengthen
contract language protecting employees
from employer subcontracting of work,
and create a procedure for alerting the
union of workers’ compensation claims
that the hotels have denied. The pact
also includes changes in language deal
ing with sick leave, vacations, and job
descriptions.
The parties’ previous agreement ex
pired on March 1, 1995, but bargaining
continued without resolution on a num
ber of noneconomic issues, including
workload, scheduling, and short-shift
premiums. These issues will be submit
ted to a labor-management committee
for possible recommendations and mid
term inclusion in the contract.
Monfort accord
Monfort, Inc. and Local 540 of the
United Food and Commercial Workers
signed a 3-year agreement covering
Monthly Labor Review
September 1995
47
Industrial Relations
some 1,800 workers at the company’s
beef slaughtering and fabrication plant
in Dumas, TX. The contract provides
wage increases, job upgrades, and im
proved pension benefits. The pact in
cludes hourly wage increases of 20
cents in the first year of the contract and
15 cents in the second and third years.
To stem a high turnover rate at the
plant, some 900 to 1,000 workers in the
bargaining unit also will receive job up
grades resulting in wage increases
ranging from 20 to 70 cents per hour,
with the amount depending on the em
ployee’s job classification. In addition,
the accord stretches out the wage pro
gression for maintenance workers, re
sulting in a $3.05 per hour difference
(was $2) between the base rate and the
top rate. At the expiration of the prior
agreement, the hourly base wage rate
was $8.55 in the processing department
and $8.85 in the slaughter and mainte
nance departments.
Other terms increase the company
contribution to the 401 (k) savings plan
from $60 a year to two-thirds of an
employee’s investment, which is lim
ited to 6 percent of annual gross wages;
implement new methods of monitoring
work time in the slaughter division; and
48
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Federal Reserve Bank of St. Louis
add 100-percent reimbursement for
doctor’s office visits and medical treat
ment for pregnancy, contingent on the
patient visiting a doctor at least once a
month during pregnancy, and continue
80-percent reimbursement for all other
doctor’s office visits.
Supreme Court rules
on affirmative action
In Adarand Constructors, Inc. v. Pena,
the Supreme Court examined the Fed
eral Government’s authority to imple
ment affirmative action programs. In its
decision, the Court held that “federal
racial classifications, like those of a
State, must serve a compelling govern
ment interest, and must be narrowly tai
lored to further that interest.” The court
added, “(A)ny person, of whatever race,
has the right to demand that any gov
ernmental actor subject to the Constitu
tion justify any racial classification sub
jecting that person to unequal treatment
under the strictest judicial scrutiny.”
The petitioner, Adarand Construc
tors, Inc., is a Colorado-based construc
tion company specializing in guard rail
work. In 1989, Adarand, a nonminority
owned firm, bid as a subcontractor for
September 1995
the guard rail portion of a construction
contract that had been awarded to Moun
tain Gravel & Construction Company by
the Central Lands Highway Division,
currently part of the Department of
Transportation. Even though Adarand
submitted the lowest bid, it lost the con
tract to Gonzales Construction Com
pany, a minority owned firm. Mountain
Gravel accepted Gonzales’ bid instead
of Adarand’s because under Federal law
it would receive additional funds for us
ing a minority owned (“disadvantaged”)
company as a subcontractor. Without the
extra payment, Mountain Gravel said it
would have selected Adarand for the
work. Adarand sued, claiming that the
presumption behind giving preference
to all minorities—that they are “socially
and economically disadvantaged” by
definition—discriminates on the basis
of race, thus violating the Fifth Amend
ment, which gives each individual equal
protection under the law.
The District Court found for the re
spondents, as did the Court of Appeals.
After review, the Supreme Court va
cated the Court of Appeal’s decision
and remanded the case to the lower
courts for further consideration “con
sistent with its opinion.”
□
Workplace Perfomance
Workplace practices,
company performance,
and unionization
Two major questions are addressed in a
study by William N. Cooke in the July
1994 Industrial and Labor Relations
Review: do employee-participation pro
grams and group-based pay incentives
have an effect on company performance
and, if so, does the effect vary across
union and nonunion companies?
According to Cooke, employee-par
ticipation programs are based on the as
sumption that front-line workers have
more complete information about work
processes and are better able to orga
nize tasks and identify obstacles to high
performance than managers. Groupbased pay incentives, such as profit and
gain sharing, are based on the assump
tion that by linking earnings to perfor
mance, employees will adjust their ef
fort to optimize income. Employees
also have an incentive to work coopera
tively, as bonuses based on profit or
other performance measures are tied to
work force effort.
Cooke suggests that a combination
of employee-participation programs
and group-based pay incentives could
exceed the gains of either one alone.
Employees would have little reason to
share performance-increasing knowl
edge with management without finan
cial incentives. Conversely, employees
with little participation in workplace
decisions cannot respond effectively to
such incentives.
How might unionization affect em
ployee-participation program s and
group-based pay incentives? Cooke pro
vides hypotheses that unions establish
a more direct and open channel for a
collective voice, which may insure that
employee-participation programs are
shaped with greater employee input.
This, along with the longer term em
ployment relationship and narrower pay
differentials in union settings, may in-
"Workplace Performance" is prepared by
Polly A. Phipps of the Office of Publica
tions and Special Studies, Bureau of La
bor Statistics.
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Federal Reserve Bank of St. Louis
crease commitment to employee partici
pation. Alternatively, existing contract
language, insistence on voluntary par
ticipation and confrontational negotia
tions may work against employee par
ticipation programs in union settings.
Cooke’s survey of Michigan manu
facturing companies provides fairly
strong evidence that both employeeparticipation program s and groupbased pay incentives increase company
performance, defined as value added
net of labor cost per employee. He also
finds strong differences by union/nonunion status, some contrary to expecta
tions. Analyzing various combinations
of work teams, group-based pay incen
tives, and union status, Cooke finds that
unionized companies with work teams
and no group pay incentives achieve the
highest level of performance—35 per
cent higher than comparable nonunion
companies with no teams or group pay.
Four other combinations attain a level
of performance 18-21 percent higher:
union and nonunion companies with
both group incentives and work teams,
and union and nonunion companies
with group incentives and no work
teams. Finally, unionized companies
without work teams or group incentives
achieve a 13 percent higher level of per
formance compared to nonunion com
panies without teams or groups incen
tives, or nonunion companies with
work teams, but no group incentives.
Based on his findings, Cooke suggests
that unionized companies may have an
environment which taps employee-par
ticipation programs most effectively,
and nonunion companies are more ef
fective in tapping the incentive effects
of group-based pay.
Work organization
and training
Paul Osterman, reporting in the April
1995 Industrial Relations, tackles the
question of whether firms that utilize
high-performance workplace practices
provide more training to their employ
ees than other firms. Osterman first
provides an interesting discussion of
the debate on skill, performance, and
training, beginning with deskilling
theories in the 1970's and 1980's,
through the current literature that sug
gests that technology can be used in dif
ferent ways and with different impacts
on skill. The focus now is directed to
ward the pace of upskilling and the cir
cumstances under which it occurs. The
link between skill and training is criti
cal for high-performance work, because
increased training is usually necessary
to reap any productivity gains.
Osterman surveyed 875 establish
ments to assess the relationship be
tween skill, training, and high-perfor
mance workplace systems. His survey
focuses on an establishment’s “core”
employees, defined as the largest group
of nonsupervisory, nonmanagement
workers at the location. He finds a
strong trend in upskilling for professional/technical employees, and a less
pronounced, but upward trend in com
plex work for blue-collar workers. For
professional/technical workers, the
change in skill is due to increased com
puter usage, while for blue-collar work
ers, the change is behavioral, such as
increased interpersonal and cognitive
skills.
Osterman uses off-the-job training as
his measure of training because more
comprehensive concepts of training are
difficult to measure, due to limited es
tablishment records and because much
training is on-the-job and informal. He
finds that professional/technical core
employees are more likely to receive
off-the-job training than are blue-col
lar employees. Blue-collar employees at
larger establishments fare better in re
ceiving off-the-job training; the size ef
fect does not hold for professional/tech
nical employees.
Osterman also asks about the use of
five workplace practices in relation to
core employees: self-directed work
teams, job rotation, employee problem
solving groups, statistical process con
trol, and total quality management. Us
ing a multivariate regression model, he
finds that the use of these high-perfor
mance systems is associated with in
creased training effort.
Monthly Labor Review
September 1995
49
Workplace Performance
In conclusion, Osterman points out
that while work organization appears
to drive training, it could be the case
that establishments engaging in more
training find it easier to adopt high-per
formance systems. His data provide evi
dence for the former hypothesis, as sur
vey respondents indicate that some
years after introducing new work sys
tems, training efforts plateau, although
he notes the necessity of longitudinal
data to answer this question.
Assessing employee
involvement programs
John L. Cotton provides a comprehen
sive guide to the vast literature on em
ployee involvement in his 1993 book,
Employee Involvement: Methods fo r
Improving Performance and Work Atti
tudes. Cotton begins with the history of
employee involvement and a review of
theories and models. He then turns to
specific techniques designed to achieve
employee involvement, including qual
ity of work life programs, quality circles,
gainsharing plans, representative par
ticipation, job enrichment, work teams
and employee ownership. In chapters on
each form of employee involvement,
Cotton proves a concrete example of a
firm using the technique in his descrip
tion. He then reviews and summarizes
research findings and discusses imple
mentation issues, integrating scientific
findings and applied advice.
In one of the final chapters, Cotton
categorizes employee-involvement tech
niques into those with strong (self-di
rected work teams, gainsharing), inter
mediate (quality of work life, job en
richment, employee ownership), and
weak (quality circles, representative
participation) effects, based on his re
view. Successful techniques have four
major features: involvement is directed
on everyday work, employees have a
degree of control to make decisions, im
provements can be initiated by employ
ees, and more successful techniques re
quire major changes in an employee’s
work life. Cotton points out that while
50
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outcomes differed across various tech
niques, recommended processes for in
volvement did not. These processes
include: management commitment,
employee training, and management
education.
Computer integration
and enterprises
Computer integration of the different
functions of an enterprise has been pro
gressing for the last 40 years, accord
ing to Eric Alsene, writing in the 1994
International Labour Review. The first
concept of computerized integration in
the 1950's and 1960's involved a “total
system” to electronically integrate all
activities, including design, production,
management, marketing and finance.
Since then, a number of different con
cepts, including programs feeding off a
central data base, modular systems, and
“islands” of computerization linking
administrative units of enterprises, have
emerged.
However, most studies on computer
ized integration speculate on what
should or might happen—“virtual cor
porations,” “extended enterprises,”
“new corporate cultures,”—rather than
collecting and analyzing data. Alsene,
in contrast, conducts case studies of two
up-and-running systems in order to as
sess the actual effects of computerized
integration in enterprises. His cases in
cludes a hospital dietary system that
links two departments and an inte
grated maintenance-management sys
tem linking three administrative units
of a industrial headquarters and plant.
Alsene analyzes the before and after
content and organization of work, op
erational management style and control
systems, staffing, hierarchies and orga
nizational culture through observation
and interviews.
His results in the hospital setting
suggest an upgrading of the work of
dietitians, through the elimination of
certain routine tasks, which free them
to concentrate on professional duties.
September 1995
However, technicians and clerks in the
dietary unit experience a narrowing of
their tasks and reduction in numbers.
In patient-care units, head nurses take
on the task of entering standardized
codes into the system, a downgrading
of their job, as the task was originally
carried out by assistant nurses more in
formally over the telephone. These lat
ter two examples are contrary to the
speculation that integration always
leads to job enrichment.
Alsene finds a different result for
work content in the industrial company,
where the computerized system affects
the accounts payable, procurement, and
maintenance supervision departments.
The work of clerks in accounts payable
and procurement becomes less repeti
tive and monotonous. For example,
the payment slips filled out in several
copies are eliminated, a predicted trans
formation. However, other aspects of
their work becomes more standardized
and less flexible, as they must follow
established procedures. However, new
tasks are added to their workload, and
with the most tedious tasks eliminated,
the changes result in clerks identifying
more with the objectives of the enter
prise.
Alsene thus sees confirmation of
some elements of predicted change due
to computerized systems in both cases,
including the emergence of new com
puter-specialist occupations, the facili
tation of the verification of orders and
purchases, and reduction of office work
towards more professional tasks for
dietitians, and office and maintenance
supervisors, at the industrial company.
Alsene also asserts that the changes he
considers more positive occur through
integration by a common data base in
the industrial company, as opposed to
integration by interface, in the hospital
setting. He suggests that integration by
interface leads to emergence of routine
tasks, while integration through a com
mon data base lessens horizontal bound
aries of the organizations, and produces
a new form of communication between
people and data.
□
Book Reviews
After the fall
Trade Union Growth and Decline: An
International Study. By Walter
Galenson. Westport, c t , Praeger,
1994, 176 pp. $49.95.
Why has there been a decline in union
ization in most industrial nations?
What has happened to unions in devel
oping countries? And what is the fu
ture of trade unionism?
Trade Union Growth and Decline:
An International Study, by Walter
Galenson, professor emeritus of indus
trial relations at Cornell University and
a top expert in comparative interna
tional labor movements, reports his
research on causes of trade union
growth and decline in the 1980’s. His
measure of “union density” is the ratio
of trade union membership to the labor
force.
As with other variables Galenson
explores, he warns of difficulties in both
parts of the ratio. In fact, for experts in
comparative labor movements, Galenson’s methods will be more interesting
than his results. He recognizes the dif
ficulties of dealing with deficient data,
but he brings subjective judgments and
regression analysis to measure the im
pact on union density of government
policies toward unions, the quality of
union services to members, employer
attitudes, and public opinion.
Galenson finds general decline in
trade union membership as a percent
of employed wage and salary workers
in 13 industrial countries he examines,
with the exception of Norway and Swe
den. The other nations include Austra
lia, Canada, Denmark, France, Germany,
Italy, Japan, New Zealand, Spain, the
United Kingdom, and the United States.
By contrast, in 12 developing coun
tries—Argentina, Brazil, Chile, Egypt,
India, Kenya, Korea, Malaysia, Mexico,
the Philippines, Taiwan, and Thai
land—he finds a much more mixed pic
ture: Big gains in union membership as
a percent of the labor force in Korea and
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Federal Reserve Bank of St. Louis
Taiwan after the introduction of more
political democracy in 1987, some sta
bility elsewhere, and “catastrophic” de
clines under authoritarian governments
in Chile and Kenya.
Only at the extremes of pro-union or
anti-union government policies is there
an effect on union density, says Galen
son. But the role of government “is
more important to developing coun
tries, where unions are fragile and tend
to be pawns in political struggles.”
The relative shift of employment
from manufacturing to services ac
counts for much of the union member
ship losses in most industrial nations,
Galenson writes. “But the question is
why employees in the service sector
have not joined unions in sufficient
numbers to offset the losses in manu
facturing.”
After examining effects of earnings,
inflation, unemployment, and female
employment, Galenson finds that “the
only factor that proved to be significant
was unemployment in the industrial
countries.”
The quality of union services—rep
resentation of members in bargaining
and grievances, independence of gov
ernment or employer domination, union
financial resources, and freedom from
corruption—appears to have some posi
tive effect on union density in indus
trial countries but not in developing
countries, according to Galenson. He
speculates that although union quality
is important in developing countries, it
is overshadowed by other factors, such
as the role of government (pro-union,
neutral, or anti-union) and employer
hostility.
Employer hostility to unions is not
a major factor in the decline in union
density in industrial nations, Galenson
claims: “In any event, except perhaps
in developing countries in which em
ployers contribute to the suppression
of union activity, the decline in union
density, where it has taken place, can
not be attributed to growing employer
antipathy.”
Public opinion doesn’t help Galen
son explain union density. For example,
he does not find useful public opinion
surveys providing information in devel
oping countries. However, a chapter on
public opinion polls in industrial na
tions presents interesting findings. “The
data do not reveal any consistent rela
tionship between general public atti
tudes and union density,” he writes.
In the final chapter, Galenson argues
that “unions were the victims of their
own success...The rise of the welfare
state— the expansion of government
programs and services—reduced the
appeal of unionism by generalizing the
benefits that had attracted employees in
the past. When potential members be
gan to weigh the costs of joining unions
against the anticipated benefits, they
began to stay out.”
Galenson concludes that “continued
reliance on traditional appeals are not
likely to serve the cause of trade union
ism well.” Participation in enterprise
decisionmaking is a growing issue for
workers: “Unions that do not press for
participatory schemes are denying
themselves a potent organizing wea
pon.” He sees skilled workers, service
workers, and women as good targets for
union organizing efforts. But he notes
that unions in developing countries
have a long way to go before the tradi
tional union focus on wages and hours
loses its appeal.
Galenson’s report is far richer in
detail than outlined here. I think he
wrongly ignores the mobility of capital
that helps employers avoid unions and
underestimates anti-union employer
behavior in the United States. Never
theless, his findings merit the attention
of anyone interested in the future of
unions in the United States and other
nations.
—Markley Roberts
Economic Research Department
Monthly Labor Review
A F L -C IO
September 1995
51
Book Reviews
Publications received
Economic and social statistics
Abowd, John M ., Francis Kramarz, and
Antoine Moreau, P r o d u c t Q u a lity a n d
W o rk er Q u a lity . Cambridge, ma , Na
tional Bureau of Economic Research,
Inc., 1995, 227 pp. (Working Paper
5077.) $5 per copy, plus $10 for postage
and handling-outside the United States.
Israel Central Bureau of Statistics, M on th ly
B u lletin o f S ta tistic s, and S u p p lem en t,
March 1995. Jerusalem, Israel Central
Bureau of Statistics, 128 and 248 pp.,
respectively.
U.S. Department of Health and Human Ser
vices, In co m e o f th e A g e d C h a rtb o o k ,
1992. Washington, U.S. Department of
Health and Human Services, Social Se
curity Administration, Office of Research
and Statistics, 1994, 23 pp. Stock No.
017-070-00464-4. $2. For sale by the
Superintendent of Documents, Mail Stop
ssop, Washington, DC 20402-9328.
Economic growth
and development
Bloom, David E. and Ajay S. Mahal, D o e s
the aids E p id em ic R e a lly T hreaten E c o
n o m ic G ro w th ? Cambridge, ma, National
Bureau of Economic Research, Inc.,
1995, 35 pp. (Working Paper 5148.) $5
per copy, plus $10 for postage and han
dling outside the United States.
Ehrenberg, Ronald G ., Paul J. Pieper, and
Rachel A. Willis, W ould R edu cin g Ten
ure P ro b a b ilitie s In crease F acu lty S a la
ries? Cambridge, ma, National Bureau
of Economic Research, Inc., 1995,28 pp.
(Working Paper 5150.) $5 per copy, plus
$10 for postage and handling outside the
United States.
Mincer, Jacob, In vestm en t In U.S. E d u c a
tion a n d Training. Cambridge, ma, Na
tional Bureau of Economic Research,
Inc., 1994,57 pp. (Working Paper 4844.)
$5 per copy, plus $10 for postage and
handling outside the United States.
Health and safety
Leigh, J. Paul, C a u ses o f D ea th in the W ork
p la c e . Westport, ct, Quorum Books,
1995, 328 pp. $59.95.
U .S. Bureau of Labor Statistics, O c c u p a
tio n a l I n ju rie s a n d I lln e s s e s : C ou n ts,
R ates, a n d C h a ra cte ristic s, 1992. Wash
ington, 1995, Bulletin 2455, 265 pp.
Stock No. 029001-03143-2. $6. For sale
by the Superintendent of Documents,
Mail Stop ssop, Washington 20402-9328.
In tra sch o o l V ariation in C la ss S ize: P a t
tern s a n d Im plication s. Cambridge, ma ,
National Bureau of Economic Research,
Inc., 1995,34 pp. (Working Paper 5144.)
$5, per copy, plus $10 for postage and
handling outside the United States.
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Federal Reserve Bank of St. Louis
D ir e c to r y o f T exas M a n u fa c tu re rs, 1 9 9 5 :
Vol. 1, A lp h a b e tic a l a n d G e o g ra p h ic a l
S ectio n s. Vol. II, P ro d u c t S ectio n a n d
Index. Austin, University of Texas at
Austin, Bureau of Business Research,
Graduate School of Business, 1995, 509
and 710 pp., respectively. $130.
Gansler, Jacques S., D e fen se C o n v e rsio n :
Cambridge, ma , The
277 pp. $25.
mit
Press, 1995,
Niskanen, William A ., Jr. B u rea u cra cy a n d
P u b lic E con om ics. Brookfield, vt, Ed
ward Elgar Publishing, Ltd., 1994, 298
pp. $67.95.
Lowitt, Richard, ed., P o litic s in th e P o s t
w a r A m eric a n West. Norman, ok, Uni
versity of Oklahoma Press, 1995,400 pp.
$19.95, paper.
C r a f t J u r is d ic tio n A g r e e m e n ts , 1 9 9 5
E dition. Washington, 1995, 221 pp. $45,
paper. Available from BNA Books,
Edison, nj.
of Economic Research, Inc., 1995,20 pp.
(Working Paper 5105.) $5 per copy, plus
$10 for postage and handling outside the
United States.
Altonji, Joseph G. and Thomas A. Dunn,
Boozer, Michael and Cecilia Rouse,
Industiy and government
organization
Bureau of National Affairs, C o n s tru c tio n
B a rg a in in g L e g isla tio n on S trik e s a n d
W ages. Cambridge, ma, National Bureau
Cambridge, ma, National Bureau of Eco
nomic Research, Inc., 1995, 48 pp.
(Working Paper 5072.) $5 per copy, plus
$10 for postage and handling outside the
United States.
Press, 1994, 192 pp. $39.95.
Labor and economic history
ies on R eform a n d P o stco m m u n ist T ran
sition. Cambridge, ma , The MIT Press,
The E ffects o f S ch o o l a n d F a m ily C h a r
a c te r is tic s on th e R etu rn to E du cation .
U n ion s a n d the S ta te in P en in su la r M a
la ysia . New York, Oxford University
Industrial relations
Komai, Janos, H ig h w a y a n d B yw a ys: S tu d
Education
Jomo, K. S. and Patricia Todd, T ra d e
T ransform in g the A rs e n a l o f D em ocra cy.
Cramton, Peter C ., Morley Gunderson, Jo
seph S. Tracy, The E ffect o f C o lle c tiv e
1995, 264 pp. $29.95.
New York, Oxford Uni
versity Press, 1995, 231 pp. $39.95.
b a l E conom y.
Gruenberg, Gladys W., A r b itr a tio n 1 9 9 4 :
C o n tr o v e rsy a n d C on tin u ity. (Proceed
ings of the Forty-Seventh Annual Meet
ing, National Association of Arbitrators.)
Washington, Bureau of National Affairs
Inc., 1994, 396 pp. $40. Available from
BNA Books, Edison, nj.
May, Dawn, A b o r ig in a l L a b o u r a n d th e
C a ttle In dustry: Q u een sla n d fro m W hite
S e ttle m e n t to th e P resen t. New York,
Cambridge University Press, 1994, 242
pp. $59.95.
Miller, Sally M. and Daniel A. Comford,
A m eric a n L a b o r in the E ra o f W orld W ar
II. Westport, ct , Praeger Publishers,
1995, 240 pp. $59.95, cloth; $18.95,
paper.
Wellman, David, T h e U n io n M a k e s U s
S tro n g : R a d ic a l U n io n ism on th e San
F ra n cisco W aterfront. New York, Cam
bridge University Press, 1995, 364 pp.
$59.95.
Hauck, Vern E ., ed., A r b itr a tin g S e x u a l
H a ra ssm e n t C ases. Washington, Bureau
of National Affairs, Inc., 1995, 511 pp.
$95, paper.
Cohen, Malcolm S., L a b o r S h o rta g es: A s
Jacoby, Sanford M ., ed., The W o rkers o f
A m e r ic a A p p r o a c h e s th e T w e n ty -F irst
C e n tu r y . Ann Arbor, University of
N a tio n s: In d u stria l R e la tio n s in a G lo -
September 1995
Labor force
Michigan Press, 1995, 183 pp. $37.50.
Davis, Steven J. and John Haltiwanger, M e a
su r in g G r o s s W o rk er a n d J o b F lo w s.
Cambridge, ma, National Bureau of Eco
nomic Research, Inc., 1995, 50 pp.
(Working Paper 5133.) $5 per copy, plus
$10 for postage and handling outside the
United States.
Dulude, Louise, S en io rity a n d E m p lo ym en t
E q u ity F o r Women. Kingston, Ontario,
Queen’s University, Industrial Relations
Center, irc Press, 1995, 154 pp.
Hagan, John and Fiona Kay, G e n d e r in P r a c
tic e : A S tu d y o f L a w y e r s ’ L iv e s . New
York, Oxford University Press, 1995,235
pp. $35.
A n a ly sis w ith an A p p lic a tio n to the D e
m a n d f o r Fish. Cambridge, ma, National
Bureau of Economic Research, Inc.,
1995, 43 pp. (Technical Working Paper,
178.) $5 per copy, plus $10 for postage
and handling outside the United States.
Brown, Kenneth H. and Shane M .
Greenstein, H o w M u ch B e tte r Is Bigger,
F a s te r a n d C h e a p e r ? B u y e r B e n e fits
From In n ovation in M ain fram e C o m p u t
e rs in the 1980s. Cambridge, ma, National
Bureau of Economic Research, Inc.,
1995, 78 pp. (Working Paper 5138.) $5
per copy, plus $10 for postage and han
dling outside the United States.
Diewert, W. Erwin, A x io m a tic a n d E c o
Huws, Ursula, ed., A ctio n P ro g ra m m es F o r
the P ro tectio n o f H om ew o rk ers: Ten C a se
S tu d ies F rom A ro u n d the W orld. Geneva,
International Labor Office, 1995,142 pp.
$16, paper. Available from ilo Publica
tions Center, Albany, ny .
Republic of China, M o n th ly B u lle tin o f
M a n p o w e r S ta tistics, T aiw an A rea, F e b
ru a ry 1995. Taiwan, Republic of China,
Office of Directorate-General of Budget,
111 pp.
W orkforce P o lic ie s : S ta te A c tiv ity a n d In
novation s. Washington, National Asso
ciation of State Budget Officers, 1995,
132 pp. $25, paper.
Management and organization
theory
Aubrey, Robert and Paul M. Cohen, W ork
ing W isd o m : T im e le ss S k ills a n d Van
g u a rd S tra te g ie s f o r L ea rn in g O rg a n iza
tions. San Francisco, Jossey-Bass Pub
lishers, 1955, 192 pp. $25.
Hitchcock, Darcy E. and Marsha L. Willard,
W hy T eam s C an F a il A n d W h at to D o
A b o u t It: E s s e n tia l T o o ls f o r A n y o n e
Im plem en tin g S e lf-D ire cted W ork Team s.
Burr Ridge, il, Irwin Professional Pub
lishing, 1995, 30 pp. $30.
Lewin, David and Daniel J. B. Mitchell,
H um an R eso u rce M an agem en t: An E c o
n o m ic A pp ro a ch . 2 d ed., Cincinnati, oh,
South-Western College Publishing, 1995,
760 pp.
Prices and living conditions
Angrist, Joshua D., Kathryn Graddy, Guido
W. Imbens, N o n - P a r a m e tr ic D e m a n d
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Federal Reserve Bank of St. Louis
n om ic A p p ro a c h e s to E lem e n ta ry P ric e
In dexes, Cambridge, ma, National Bureau
of Economic Research, Inc., 1995, 60 pp.
(Working Paper 5104.) $5 per copy, plus
$10 for postage and handling outside the
United States.
__________ P ric e a n d Volume M easu res in the
S ystem o f N a tio n a l A ccou n ts, Cambridge,
ma , National Bureau of Economic Re
search, Inc., 1995, 63 pp. (Working Pa
per 5103.) $5 per copy, plus $10 for post
age and handling outside the United
States.
Productivity and technological
change
Wages and compensation
Dickens, William T., D o L a b o r R en ts J u s
t if y S t r a t e g i c T r a d e a n d I n d u s t r i a l
P o lic y ? Cambridge, ma, National Bureau
of Economic Research, Inc., 1995,44 pp.
(Working Paper 5137.) $5 per copy, plus
$10 for postage and handling outside the
United States.
DiNardo, John, Nicole M. Fortin, Thomas
Lemieux, L a b o r M a rk e t In stitu tio n s a n d
the D istrib u tio n o f W ages, 1 9 7 3 -1 9 9 2 :
A S e m ip a ra m e tric A p p ro a ch . Cambridge,
National Bureau of Economic Re
search, Inc., 1995, 62 pp. (Working Pa
per 5093.) $5 per copy, plus $10 for post
age and handling outside the United
States.
ma,
Mumane, Richard J., John B. Willett, and
Frank Levy, The G ro w in g Im p o rta n ce o f
C o g n itiv e S kills in W age D eterm in a tio n .
Cambridge, ma, National Bureau of Eco
nomic Research, Inc., 1995, 46 pp.
(Working Paper 5076.) $5 per copy, plus
$10 for postage and handling outside the
United States.
Neal, Derek A. and William R. Johnson, The
R o le o f P r e -M a r k e t F a c to r s in B la ck W hite W age D ifferen ces. Cambridge, ma,
National Bureau of Economic Research,
Inc., 1995, 49 pp. (Working Paper 5124.)
$5 per copy, plus $10 for postage and
handling outside the United States.
Helpman, Elhanan and Manuel Trajtenberg,
A T im e To S o w a n d a T im e to R e a p :
G row th B a se d on G e n e ra l P u rp o se Tech
nologies. Cambridge, ma, National Bu
reau of Economic Research, Inc., 1994,
43 pp. (Working Paper 4854.) $5 per
copy, plus $10 for postage and handling
outside the United States.
Henderson, Rebecca, Adam B. Jaffe, Manuel
Trajtenberg, U n iversities a s a Sou rce o f
C o m m e r c ia l T e c h n o lo g y : A D e t a il e d
A n a ly sis o f U n iversity P a ten tin g, 1 9 6 5 1988. Cambridge, ma, National Bureau
of Economic Research, Inc., 1995, 39 pp.
(Working Paper 5068.) $5 per copy, plus
$10 for postage and handling outside the
United States.
U.S. Bureau of Labor Statistics, P ro d u c tiv
Neumark, David and William Wascher, The
E ffects o f M in im u m W ages on T een age
E m p lo y m en t a n d E n rollm en t: E v id e n c e
F rom M a tc h e d c p s S u rveys. Cambridge,
National Bureau of Economic Re
search, Inc., 1995, 49 pp. (Working Pa
per 5092.) $5 per copy, plus $10 for post
age and handling outside the United
States.
ma ,
Welfare programs and social
insurance
Brechling, Frank and Louise Laurence, P e r
m a n en t J o b L o ss a n d the U.S. S ystem o f
F in a n c in g U n e m p lo y m e n t In su ra n c e .
Kalamazoo, mi, W.E. Upjohn Institute for
Employment Research, 1995, 111 pp.
ity M ea su res f o r S e le c te d In d u stries a n d
G o vern m en t S ervices. Washington, Bul
Burton, John F., Jr. and Timothy P. Schmidle,
letin 2461, Stock No. 029-001-03211-1.
$10. For sale by the Superintendent of
Documents, Mail Stop SSOP, Washing
ton, D C 20402-9328.
Horsham, pa, lrp Publications, 1995,552
pp. $58.90, plus $4.50, shipping and han
dling, paper.
1 9 9 5 W o rk ers’ C om p en sa tio n Y ear B ook.
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Book Reviews
Card, David and Brian P. McCall, Is W ork
e r s ’ C o m p en sa tio n C o v erin g U n in su red
M e d i c a l C o s t s ? E v id e n c e f r o m th e
‘M o n d a y E ffect. ’ Cambridge, ma , Na
tional Bureau of Economic Research,
Inc., 1995,45 pp. (Working Paper 5058.)
$5 per copy, plus $10 for postage and
handling outside the United States.
Hoynes, Hilary Williamson, D o e s W elfare
P la y A n y R o le in F em ale H ea d sh ip D e
c isio n s? Cambridge, ma , National Bu
reau of Economic Research, Inc., 1995,
48 pp. (Working Paper 5149.) $5 per
copy, plus $10 for postage and handling
outside the United States.
Rosen, Sherwin, P u b lic E m ploym en t, Taxes
a n d the W elfare S ta te in S w ed en . Cam
bridge, ma, National Bureau of Economic
Research, Inc., 1995, 59 pp. (Working
Paper 5003.) $5 per copy, plus $10 for
postage and handling outside the United
States.
Thomason, Terry and Richard P.
Chaykowski, eds., R esea rch in C anadian
W o r k e r s ’ C o m p e n s a t i o n . Kingston,
Ontario, Queen’s University, Industrial
Relations Center, IRC Press, 1995, 224
pp. $40.
Ruhm, Christopher J. and Jackqueline L.
Teague, P a re n ta l L ea v e P o lic ie s In E u
rope a n d N orth A m erica . Cambridge, ma,
National Bureau of Economic Research,
Inc., 1995,33 pp. (Working Paper 5065.)
$5 per copy, plus $10 for postage and
handling outside the United States.
Turner, John and Noriyasu Watanabe, Pri
vate P en sio n P o lic ie s in In d u stria lize d
C o u n tr ie s : A C o m p a r a tiv e A n a ly s is .
Kalamazoo, Ml, W.E. Upjohn Institute for
Employment Research, 1995, 170 pp.
$14, paper.
U.S. Railroad Retirement Board, N in eteen th
Schmitt, Ray, ed. The Future o f P en sio n s in
the U n ited States. Philadelphia, Univer
sity of Pennsylvania Press, Pension Re
search Council, the Wharton School,
1993, 317 pp., $39.
A c tu a r ia l V alu ation o f th e A s s e ts a n d
L ia b ilitie s U n d e r th e R a ilr o a d R e tir e
m en t A c ts a s o f D e c e m b e r 3 1 ,1 9 9 2 , with
Technical Supplement. Chicago, il, U.S.
Railroad Retirement Board, Bureau of
the Actuary, 1994, 99 pp.
□
LABSTAT Available via World Wide Web
l a b s t a t , the Bureau of Labor Statistics public database, provides current and his
torical data for many b l s surveys as well as numerous news releases.
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
pages. Access to l a b s t a t data and news releases is provided by a link to the b l s
gopher server. The URL is:
http://stats.bls.gov/blshome.html
If you have questions or comments regarding the LABSTAT system on the
Internet, address e-mail to:
labstat.helpdesk @bls.gov
54
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September 1995
Current Labor Statistics
Notes on Labor Statistics................. 56
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...........................................................
66
67
67
Labor force data
4. Employment status of the population,
seasonally adjusted.................................................................
5. Selected employment indicators,
seasonally adjusted.................................................................
6. Selected unemployment indicators,
seasonally adjusted.................................................................
7. Duration of unemployment,
seasonally adjusted.................................................................
8. Unemployed persons by reason for unemployment,
seasonally adjusted.................................................................
9. Unemployment rates by sex and age,
seasonally adjusted.................................................................
10. Unemployment rates by States,
seasonally adjusted.................................................................
11. Employment of workers by States,
seasonally adjusted.................................................................
12. Employment of workers by industry,
seasonally adjusted.................................................................
13. Average weekly hours by industry,
seasonally adjusted.................................................................
14. Average hourly earnings by industry,
seasonally adjusted.................................................................
15. Average hourly earnings by industry....................................
16. A verage w eek ly earnings by in d u str y .....................................
17. Diffusion indexes of employment change,
seasonally adjusted.................................................................
18. Annual data: Employment status of the population........
19. Annual data: Employment levels by industry.....................
20. Annual data: Average hours
and earnings levels by industry..........................................
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27. Average specified compensation and wage rate
changes, bargaining agreements covering
1,000 workers or more...........................................................
28. Specified changes in cost of 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............
87
88
89
89
68
69
70
70
71
71
72
72
73
75
75
76
77
78
78
79
79
Labor compensation and collective
bargaining data
21. Employment Cost Index, compensation,
by occupation and industry group.....................................
22. Employment Cost Index, wages and salaries,
by occupation and industry group.....................................
23. Employment Cost Index, benefits, private industry
workers, by occupation and industry group...................
24. Employment Cost Index, private nonfarm workers,
by bargaining status, region, and area size .....................
25. Participants in employer-provided benefit plans.............
26. Specified compensation and wage rate changes
from contract settlements, and effective wage
rate changes, agreements covering 1,000
workers or more.......................................................................
Labor compensation and collective
bargaining data—Continued
Price data
31. Consumer Price Index: U.S. city average, by expenditure
category and commodity and service groups.................. 90
32. Consumer Price Index: U.S. city average and
local data, all items................................................................ 93
33. Annual data: Consumer Price Index, all items
and major groups..................................................................... 94
34. Producer Price Indexes by stage of processing.................. 95
35. Producer Price Indexes for the net output of major
industry groups..................................................... .................. 96
36. Annual data: Producer Price Indexes
by stage of processing............................................................. 96
37. U.S. export price indexes by Standard International
Trade Classification................................................................ 97
38. U.S. import price indexes by Standard International
Trade Classification................................................................ 98
39. U.S. export price indexes by end-use category.................. 99
40. U.S. import price indexes by end-use category.................. 99
41. U.S.international price indexes for selected
categories of services............................................................ 100
Productivity data
42. Indexes of 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 of output per hour for selected
industries....................................................................................
100
101
101
102
International comparisons data
80
82
83
84
85
86
46. Unemployment rates in nine countries,
data seasonally adjusted........................................................ 104
47. Annual data: Employment status of the civilian
working-age population, 10 countries.............................. 105
48. Annual indexes of productivity and related measures,
12 countries............................................................................... 106
Injury and Illness data
49. Annual data: Occupational injury and illness
incidence rates.......................................................................... 107
Monthly Labor Review
September 1995
55
Notes on Current Labor Statistics
This section of the R e view presents the prin
cipal statistical series collected and calcu
lated by the Bureau of 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 of 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 R eview . Seasonally adjusted es
tablishment survey data shown in tables 1214 and 16-17 were revised in the July 1995
R e v ie w and reflect the experience through
March 1995. A brief explanation of 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 of changes in price. These adjustments
are made by dividing current-dollar values
by the Consumer Price Index or the appro
56
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priate component of the index, then multi
plying by 100. For example, given a current
hourly wage rate of $3 and a current price
index number of 150, where 1982 = 100,
the hourly rate expressed in 1982 dollars is
$2 ($3/150 x 100 = $2). The $2 (or any other
resulting 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 of 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 bls H a n dbook o f M eth o d s, Bul
letin 2414. Users also may wish to consult
M a jo r P ro g ra m s o f the B u reau o f L a b o r S ta
tistic s, 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, E m p lo y m e n t a n d
E arn in gs. Historical unadjusted data from
the household survey are published in L a
b o r F orce S ta tistic s D e r iv e d F rom the C u r
ren t P o p u la tio n S u rvey, BLS Bulletin 2307.
Historical 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 E m ploym en t, H ours,
a n d E arn ings, U n ited S ta tes, a BLS annual
bulletin. Additional information on labor
force data for sub-States are provided in the
BLS annual report, G e o g r a p h ic P r o file o f
More detailed data on consumer and pro
ducer prices are published in the monthly
periodicals, The cpi D e ta ile d R e p o r t and
P ro d u c e r P r ic e In dexes. For an overview of
the cpi reflecting 1982-84 expenditure pat
terns, see The C o n su m er P ric e Index: 1 9 8 7
R evisio n , BLS 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
P r o d u c tiv ity M e a su re s f o r S e le c te d In d u s
trie s a n d G o vern m en t S ervices, BLS Bulle
tin 2440.
For additional information on interna
tional comparisons data, see In te rn a tio n a l
C o m p a riso n s o f U n em ploym en t, BLS Bulle
tin 1979.
Detailed data on the occupational injury
and illness series are published in O c cu p a
tio n a l In ju rie s a n d Illn e sse s in th e U n ited
S tates, b y Industry, a BLS annual bulletin.
Finally, the M on th ly L a b o r R e view 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 of later
data, but may also reflect other ad
justments.
E m p lo ym en t a n d U n em ploym ent.
More detailed information on employee
compensation and collective bargaining
settlements is published in the monthly pe
riodical, C o m p en sa tio n a n d W orking C o n
ditio n s. For a comprehensive discussion of
the Employment Cost Index, see E m p lo y
m en t C o st In dexes a n d L evels, 1 9 7 5 -9 3 , BLS
Bulletin 2447. The most recent data from
the Employee Benefits Survey appear in the
following Bureau of Labor Statistics bulle
tins: E m p lo yee B en efits in M ediu m a n d L arge
F irm s; E m p lo yee B en efits in S m all P riv a te
E sta b lish m en ts; a n d E m p lo y e e B e n e fits in
S ta te a n d L o c a l G o v e r n m e n ts. Historical
data on the collective bargaining settlements
series appear in the March issue of C o m
p e n sa tio n a n d W orking C on dition s.
September 1995
Comparative Indicators
(Tables 1-3)
Comparative indicators tables provide an
overview and comparison of major bls 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 (ECl) 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 bls compensation
and wage measures because it provides a
comprehensive measure of employer costs
for hiring labor, not just outlays for wages,
and it is not affected by employment shifts
among occupations and industries.
Data on changes in com pensation,
prices, and productivity are presented in
table 2. Measures of rates of change of 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 of 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 of productivity (output per hour of
all persons) are provided for major sectors.
A lternative 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 of the series, contribute to the
variation in changes among the individual
measures.
Notes on the data
Definitions of each series and notes on the
data are contained in later sections of these
notes describing each set of data.
Employment and
Unemployment Data
(Tables 1; 4-20)
Household survey data
Description of the series
E mployment data in this section are ob
tained from the Current Population Survey,
a program of personal interviews conducted
monthly by the Bureau of the Census for the
Bureau of Labor Statistics. The sample 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 of the
sample is the same for any 2 consecutive
months.
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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 of the
month or who worked unpaid for 15 hours
or more in a family-operated enterprise and
(2) those who were temporarily absent from
their regular jobs because of illness, 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
would 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 of 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 of a major redesign of
the survey questionnaire and collection
methodology, and the introduction of
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 E m p lo ym en t a n d
E a rn in g s, 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 E m
p lo y m e n t a n d E arn ings.
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 E m p lo ym en t a n d E arn ings.
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
arim a which was developed at Statistics
Canada as an extension of the standard X11 method previously used by BLS. A de
tailed description of the procedure appears
in the X - l l arima S e a s o n a l A d ju s tm e n t
M ethod, by Estela Bee Dagum (Statistics
Canada, Catalogue No. 12-564E, January
1983).
At the end of 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 or additional information on national
household survey data, contact the Division
of Labor Force Statistics: (202) 606-6378.
Establishment survey data
Description of the series
E mployment , hours , a nd earnings data in
this section are compiled from payroll
records reported monthly on a voluntary ba
sis to the Bureau of 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 S ta n d a rd In
d u s tr ia l C la ssifica tio n (SIC) M anual. 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 of the survey
Monthly Labor Review
September 1995
57
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 establishm ent is an economic unit
which produces goods or services (such as a
factory or store) at a single location and is
engaged in one type of economic activity.
Employed persons are all persons who
received pay (including holiday and sick
pay) for any part of the payroll period 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 of 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 weekly
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
58
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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 of the R eview . 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 of 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 bls also uses the X -l 1 arima 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 coincident 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 R eview ).
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, De
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 of publication and final in the
third month. Thus, fourth-quarter data are
published as preliminary in January and
February and as final in March.
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,”
M o n th ly L a b o r R e view , December 1969,
pp. 9-20.
F or additional information on estab
lishment survey data, contact the Division
of Monthly Industry Employment Statistics:
(202) 606-6555.
lation Survey (CPS) and the Local Area Un
employment Statistics (LAUS) program,
which is conducted in cooperation with State
employment security agencies.
Monthly estimates of the labor force,
employment, and unemployment for States
and sub-State areas are a key indicator of
local economic conditions, and form the 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 of 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 of the sample
is large enough to meet bls standards of
reliability. Data for the remaining 39 States
and the District of 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 of 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 CPS
and other methodological changes. See “ Re
visions in State and Area Estimates Effec
tive January 1994,” E m p lo ym en t a n d E a rn
ings, March 1994.
F or 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 ompensation and wage data are gathered
by the Bureau from business establishments,
State and local governments, labor unions,
collective bargaining agreements on file
with the Bureau, and secondary sources.
Employment Cost Index
Unemployment data by State
Description of the series
Description of the series
The Employment Cost Index (ECI) is a
quarterly measure of the rate of change in
compensation per hour worked and includes
wages, salaries, and employer costs of em-
Data presented in this section are obtained
from two major sources— the Current Popu-
September 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 pay
ment-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, C o m p en
sa tio n a n d W orking C ondition s.
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
Monthly Labor Review
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59
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 o f 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.
60
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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 paym ents include wages and
lump-sum payments.
Contingent pay provisions are clauses
which could provide compensation changes
beyond those specified 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.
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.
September 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.
N um ber o f 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
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 D ivision o f De-
velopments in Labor-Management Rela
tions: (202) 606-6288.
Price Data
(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-ownership so that the index would reflect only the
cost of shelter services provided by owneroccupied homes. An updated cpi-U and cpiw were introduced with release of the 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
(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
S ic 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
Producer Price Indexes
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-
Monthly Labor Review
September 1995
61
Current Labor Statistics
ries are defined according to the five
digit level of detail for the Bureau of Eco
nomic Analysis End-use Classification
(SITC), and the four-digit level of detail for
the Harmonized System. Aggregate import
indexes by country or region of origin are
also available.
bls publishes indexes for selected 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.
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Federal Reserve Bank of St. Louis
Productivity Data
(Tables 2; 42-45)
Business sector and major
sectors
Description of the series
The productivity measures relate real physi
cal output to real input. As sùch, 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,
September 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—45 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.
FOR ADDITIONAL 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 b l s 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 Comparisons
(Tables 46^18)
Definitions
For the principal U.S. definitions of the la
bor force, employment, and unemploy
ment, see the Notes section dn 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 M on th ly
L a b o r R eview , 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 R eview .
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, b l s 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
Monthly Labor Review
September 1995
63
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.
64
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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.
September 1995
Occupational Injury
and Illness Data
(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 w orkday cases in volvin g 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, O ccu p a tio n a l
In ju ries a n d Illn esses in the U n ited States,
b y 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
R e co rd k ee p in g R equ irem en ts u n d er the O c
c u p a tio n a l S a fety a n d H ealth A c t o f 1970.
F or additional information on occupa
tional injuries and illnesses, contact the Di
vision of Safety and Health Statistics: (202)
606-6166.
Monthly Labor Review
September 1995
65
Current Labor Statistics: Comparative Indicators
1. Labor m arket indicators
1993
Selected indicators
1993
1994
1995
1994
III
IV
I
II
III
IV
I
II
E m p lo y m e n t d a ta 1
Employment status of the civilian noninstitutionalized population
(household survey):2
Labor force participation ra te ..................................................
Employment-population ra tio .....................................................
Unemployment rate .........................................................
Men ............................................................
16 to 24 years ..........................................................................
25 years and o v e r....................................................................
Women ......................................................................
16 to 24 years ..........................................................................
25 years and o v e r....................................................................
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
66.1
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
66.6
62.8
5.7
5.7
12.0
4.4
5.7
11.5
4.5
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
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
1-15,329
96,099
24,162
18,436
91,167
116,078
96,841
24,329
18,517
91,749
116,352
97,094
24,265
18,461
92,087
Average hours:
Private se cto r....................................................................
Manufacturing ...........................................................................
Overtime.................................................................
34.5
41.4
4.1
34.7
42.0
4.7
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
34.4
41.5
4.4
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
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
.6
.7
.5
.8
.4
Workers by bargaining status (private industry):
Union...........................................................................................
Nonunion ........................................................................
4.3
3.5
2.7
3.1
.8
.9
.8
.6
.8
1.0
.9
.8
.7
.8
.3
.4
.7
.9
.6
.7
Employment, nonfarm (payroll data), in thousands:2
E m p lo y m e n t C o s t In d e x
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.
66
Monthly Labor Review
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Federal Reserve Bank of St. Louis
September 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 com pensation, prices, and productivity
1993
1995
1994
1993
Selected measures
1994
III
IV
I
II
III
IV
.
I
II
C o m p e n s a tio n d a t a : 1, 2
Employment Cost Index-compensation (wages, salaries,
benefits):
3.5
3.6
3.0
3.1
1.0
.9
0.6
.6
0.9
1.0
0.7
.8
1.0
.8
0.4
.4
0.8
.8
0.6
.7
3.1
3.1
2.8
2.8
1.0
1.0
.6
.6
.6
.7
.7
.8
1.0
.8
.5
.5
.7
.8
.7
.7
2.7
2.7
.5
.5
1.0
.5
.9
.2
1.1
.7
.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
.7
.6
.8
2.4
1.8
.9
1.0
.3
1.5
1.1
1.3
1.3
2.8
2.1
1.9
2.2
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
2.1
2.5
1.7
3.0
3.0
-
Employment Cost Index-wages and salaries
P rice d a ta :1
Consumer Price Index (All urban consumers): All item s......
Producer Price Index:
P ro d u c tiv ity data:3
Output per hour of all persons:
I
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 Annual rates of change are computed by comparing annual averages.
3.
dexes. The data are seasonally adjusted.
4 Output per hour of all employees.
- Data not available.
Alternative m easures o f w age and com pensation changes
Four quarters ended-
Quarterly average
I
III
II
I
II
I
IV
1995
1994
1995
1994
Components
IV
III
II
I
h
Average hourly compensation:1
All persons, business sector..................................................................
All persons, nonfarm business sector...................................................
5.1
4.9
0.9
1.4
3.1
2.7
3.6
3.8
3.8
4.1
3.8
3.6
2.9
2.6
2.3
2.3
2.7
2.6
3.2
3.2
2.8
3.0
3.6
3.6
Employment Cost Index-compensation:
Civilian nonfarm 2 ..................................................................................
Private nonfarm ..................................................................................
U nion................................................................................................
Nonunion...........................................................................................
State and local governments..............................................................
.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
.6
.7
.6
.7
.4
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
2.9
2.8
2.3
2.9
3.1
.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
.7
.7
.7
.8
.2
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
3.0
2.9
2.6
3.0
3.2
.4
.1
.3
.8
.2
.6
.1
.9
.1
.7
.1
.6
.2
.3
.1
.3
.1
.2
.8
.2
.5
.1
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
2.6
.5
1.8
.3
Employment Cost Index-wages and salaries:
Civilian nonfarm2 ...................................................................................
Private nonfarm ..................................................................................
Nonunion...........................................................................................
State and local governments...............................................................
Total effective wage adjustments3 ...............................................................
From current settlements......................................................................
From prior settlements ..........................................................................
From cost-of-living provision.................................................................
(4)
(4)
Negotiated wage adjustments from settlements:3
First-year adjustments ...........................................................................
Annual rate over life of contract...........................................................
3.0
2.4
2.0
2.4
1.0
1.9
2.2
2.5
1.9
2.1
2.1
2.2
2.4
2.1
2.2
2.1
2.3
2.2
2.0
2.3
1.8
2.3
1.8
2.2
Negotiated wage and benefit adjustments from settlements:5
First-year adjustment.............................................................................
Annual rate over life of contract............................................ ■..............
3.0
2.6
3.4
2.9
(4)
1.4
1.5
2.1
1.4
1.7
1.8
1.8
3.0
2.3
3.1
2.4
3.1
2.5
2.3
2.4
2.1
2.3
1.2
1.7
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.
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Federal Reserve Bank of St. Louis
Data round to zero.
5 Limited to major collective bargaining units of 5,000 workers or more. The
most recent data are preliminary.
Monthly Labor Review
September 1995
67
Current Labor Statistics:
4.
Labor Force Data
Em ploym ent status o f the population, by sex, age, race and Hispanic origin, m onthly data seasonally adjusted
(Numbers in thousands)
Annual average
1994
1995
Employment status
1993
1994
July
Aug.
Sept.
Oct.
Nov.
Dec.
193,550
128,040
66.2
119,306
196,814
131,056
66.6
123,060
196,859
130,774
66.4
122,781
197,043
131,086
66.5
123,197
197,248
131,291
66.6
123,644
197,430
131,646
66.7
124,141
197,607
131,718
66.7
124,403
197,765
131,725
66.6
124,570
61.6
8,734
6.8
65,509
62.5
7,996
6.1
65,758
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
85,907
66,069
76.9
61,865
87,151
66,921
76.8
63,294
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
72.0
2,263
59,602
4,204
6.4
72.6
2,351
60,943
3,627
5.4
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
94,388
55,146
58.4
51,912
95,467
56,655
59.3
53,606
95,469
56,536
59.2
53,541
95,544
56,747
59.4
53,722
55.0
599
51,313
3,234
5.9
56.2
809
52,796
3,049
5.4
56.1
790
52,751
2,995
5.3
13,255
6,826
51.5
5,530
14,196
7,481
52.7
6,161
41.7
212
5,317
1,296
19.0
Jan.
Feb.
Mar.
Apr.
May
June
July
197,753
132,136
66.8
124,639
197,886
132,308
66.9
125,125
198,007
132,511
66.9
125,274
198,148
132,737
67.0
125,072
198,286
131,811
66.5
124,319
198,453
131,869
66.4
124,485
198,615
132,519
66.7
124,959
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
62.7
7,384
5.6
66,583
62.9
7,559
5.7
66,096
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
87,750
67,232
76.6
63,994
87,818
67,258
76.6
64,066
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
72.9
2,344
61,649
3,238
4.8
73.0
2,327
61,739
3,192
4.7
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
96,204
56,773
59.0
53,915
96,265
57,471
59.7
54,519
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
56.0
791
53,124
2,857
5.0
56.6
787
53,732
2,952
5.1
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
14,498
7,864
54.2
6,576
14,531
7,790
53.6
6,375
43.4
249
5,912
1,320
17.6
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
45.4
316
6,261
1,288
16.4
43.9
295
6,080
1,415
18.2
163,921
109,359
66.7
102,812
165,555
111,082
67.1
105,190
165,576
110,911
67.0
105,006
165,696 165,832
111,186 •111,381
67.1
67.2
105,401 105,740
165,954
111,555
67.2
106,010
166,072
111,637
67.2
106,242
166,175
111,715
67.2
106,352
166,361
111,876
67.2
106,366
166,444
111,830
67.2
106,604
166,521
111,999
67.3
106,698
166,613
112,153
67.3
106,500
166,708
111,568
66.9
105,935
166,822
111,541
66.9
106,145
166,931
112,197
67.2
106,770
62.7
6,547
6.0
63.5
5,892
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
63.6
5,396
4.8
64.0
5,427
4.8
22,329
13,943
62.4
12,146
22,879
14,502
63.4
12,835
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
23,221
14,707
63.3
13,142
23,249
14,656
63.0
13,033
54.4
1,796
12.9
56.1
1,666
11.5
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
56.6
1,565
10.6
56.1
1,623
11.1
TO TAL
Civilian noninstitutional
population1....................................
Civilian labor fo rce .......................
Participation rate ..................
Employed...................................
Employment-population
ratio2 ....................................
Unemployed...............................
Unemployment ra te ..............
Not in labor force ........................
M en, 20 y e a rs an d o v e r
Civilian noninstitutional
population1 ....................................
Civilian labor force........................
Participation rate ..................
Employed...................................
Employment-population
ratio2 ....................................
Agriculture...............................
Nonagricultural industries.......
Unemployed...............................
Unemployment ra te..............
W o m e n , 20 y e a rs ond o v e r
Civilian noninstitutional
population1 ....................................
Civilian labor fo rce .......................
Participation rate ..................
Employed ...................................
Employment-population
ratio2 ....................................
Agriculture...............................
Nonagricultural industries.......
Unemployed...............................
Unemployment ra te ..............
B o th s ex es, 16 to 19 ye a rs
Civilian noninstitutional
population1 ....................................
Civilian labor fo rce .......................
Participation rate ..................
Employed ...................................
Employment-population
ratio2 ...................................
Agriculture...............................
Nonagricultural industries.......
Unemployed...............................
Unemployment ra te ..............
W h ite
Civilian noninstitutional
population1 ....................................
Civilian labor force.......................
Participation rate ..................
Employed ...................................
Employment-population
ratio2 ....................................
Unemployed...............................
Unemployment rate..............
Black
Civilian noninstitutional
population1....................................
Civilian labor fo rce .......................
Participation rate ..................
Employed ...................................
Employment-population
ratio2 ....................................
Unemployed...............................
Unemployment ra te ..............
See footnotes at end of table.
68
Monthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
September 1995
4. Continued— Em ploym ent status of the population, by sex, age, race and Hispanic origin, m onthly data seasonally adjusted
(Numbers in thousands)
1995
1994
Annual average
Employment status
1993
1994
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
15,753
10,377
65.9
9,272
18,117
11,975
66.1
10,788
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
18,604
12,229
65.7
11,131
18,653
12,323
66.1
11,235
58.9
1,104
10.6
59.5
1,187
9.9
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
59.8
1,098
9.0
60.2
1,088
8.8
Hispanic origin
Civilian noninstitutional
population1 ....................................
Civilian labor fo rce .......................
Participation rate ..................
Employed ...................................
Employment-population
ratio2 ....................................
Unemployed...............................
Unemployment ra te ..............
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.
1 The population figures 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.
Selected em ploym ent indicators, m onthly data seasonally adjusted
(In thousands)
1994
Annual average
1995
Selected categories
Dec.
123,644
66,682
56,962
41,557
124,141
67,059
57,082
41,511
124,403
67,244
57,159
41,530
124,570
67,483
57,087
41,608
124,639
67,386
57,252
41,601
125,125
67,709
57,416
42,190
125,274
67,811
57,462
42,132
125,072
67,588
57,484
42,086
124,319
67,110
57,208
41,874
124,485
67,390
57,095
41,956
124,959
67,383
57,576
42,137
31,593
6,974
31,905
7,029
31,764
7,098
31,775
7,141
31,723
7,074
31,705
7,199
31,893
7,067
32,135
7,071
32,108
7,152
32,022
7,175
31,918
7,201
32,309
7,081
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
1,848
1,593
46
1,832
1,551
45
110,517
18,293
92,224
966
91,258
9,003
131
110,345
18,281
92,064
940
91,124
8,962
140
110,576
18,225
92,351
881
91,470
9,021
131
111,100
18,306
92,794
903
91,891
8,989
134
111,686
18,201
93,485
935
92,550
8,878
131
111,770
18,357
93,413
999
92,414
8,915
120
111,960
18,340
93,620
1,023
92,597
8,959
121
111,987
18,295
93,692
1,075
92,617
9,039
95
112,461
18,504
93,957
1,075
92,882
8,904
118
112,649
18,685
93,964
1,039
92,925
8,865
129
112,578
18,646
93,932
988
92,945
8,848
110
112,111
18,493
93,619
913
92,705
8,763
125
112,160
18,387
93,773
866
92,907
8,765
106
112,331
18,358
93,973
887
93,086
9,098
103
6,348
4,625
4,467
4,348
4,333
4,411
4,411
4,422
4,693
4,460
4,530
4,469
4,476
4,442
4,402
3,140
2,908
2,432
1,871
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
2,304
1,785
2,497
1,672
15,062
17,638
17,922
17,955
17,609
17,644
17,756
17,576
17,940
18,041
17,627
18,121
17,666
17,745
18,299
6,106
4,414
4,273
4,173
4,154
4,226
4,246
4,254
4,430
4,187
4,347
4,171
4,289
4,185
4,234
2,977
2,832
2,311
1,824
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
2,158
1,747
2,305
1,613
14,637
17,007
17,308
17,314
16,982
16,992
17,101
16,917
17,307
17,381
16,991
17,232
17,034
17,056
17,660
July
Aug.
119,306
64,700
54,606
40,869
123,060
66,450
56,610
41,414
122,781
66,226
56,555
41,281
123,197
66,458
56,739
41,487
30,512
6,764
31,536
7,053
31,462
7,016
1,637
1,332
105
1,715
1,645
49
107,011
18,504
88,507
1,105
87,402
9,003
218
Jan.
Feb.
Mar.
May
June
Nov.
1994
Sept.
Apr.
Oct.
1993
July
C H A R A C T E R IS T IC
Employed, 16 years and o ver......
M e n ..........................................
Women ....................................
Married men, spouse present ..
Married women, spouse
present....................................
Women who maintain families .
CLASS OF W ORKER
Agriculture:
Wage and salary w orkers.......
Self-employed workers............
Unpaid family w orkers.............
Nonagricultural industries:
Wage and salary w orkers.......
Government ..........................
Private industries...................
Private households.............
O th e r...................................
Self-employed workers............
Unpaid family workers.............
PE R S O N S A T W O R K
P A R T T IM E 1
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 .....................................
1 Excludes persons “ with a job but not at work” during the survey period for such reasons as vacation, illness, or industrial disputes.
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.
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
Monthly Labor Review
September 1995
69
Current Labor Statistics:
6.
Labor Force Data
Selected unem ploym ent indicators, m onthly data seasonally adjusted
(Unemployment rates)
Annual average
1994
1995
Selected categories
1993
1994
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
Total, all workers.....................................................
Both sexes, 16 to 19 years................................
Men, 20 years and o v e r.....................................
Women, 20 years and over................................
6.8
19.0
6.4
5.9
6.1
17.6
5.4
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
5.6
16.4
4.8
5.0
5.7
18.2
4.7
5.1
White, to ta l.........................................................
Both sexes, 16 to 19 years.............................
Men, 16 to 19 ye ars...................................
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
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
4.8
13.1
14.5
11.6
4.3
4.4
4.8
14.8
14.6
15.0
4.1
4.4
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 o ver.............................
12.9
38.9
40.1
37.5
12.1
10.6
11.5
35.2
37.6
32.6
10.3
9.8
11.2
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
10.6
37.8
38.7
36.8
9.0
8.7
11.1
39.0
41.6
36.3
9.1
9.4
Hispanic origin, to ta l...........................................
10.6
9.9
10.0
10.1
9.9
9.4
8.8
9.2
10.2
8.9
9.1
8.8
10.0
9.0
8.8
Married men, spouse present............................
Married women, spouse present.......................
Women who maintain families...........................
Full-time w orkers................................................
Part-time workers ...............................................
4.4
4.6
9.5
7.4
7.4
3.7
4.1
8.9
6.8
7.1
3.6
4.0
7.9
6.1
5.9
3.5
4.1
8.8
6.1
6.0
3.4
4.0
8.9
6.0
6.2
3.3
4.0
8.9
5.8
5.8
3.2
3.9
8.7
5.8
5.6
3.2
3.7
8.8
5.6
5.4
3.4
3.7
8.9
5.3
5.9
3.0
3.6
8.1
5.5
6.2
3.2
3.9
7.6
5.3
6.0
3.4
4.2
9.0
5.4
5.8
3.4
3.8
8.4
5.6
6.1
3.4
4.1
8.5
5.5
6.3
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
6.3
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
5.7
4.4
10.6
5.2
4.2
6.6
4.5
6.2
5.9
3.4
10.9
5.2
4.8
5.8
4.7
6.6
4.1
6.5
3.3
11.6
3.6
6.1
3.4
11.3
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
3.3
5.5
3.2
11.9
3.5
5.8
2.8
9.7
C H A R A C T E R IS T IC
3 .4 “
3.9
8.0
5.6
6.3
IN D U S TR Y
Nonagricultural private wage and salary workers ....
Mining..................................................................
Construction .......................................................
Manufacturing ....................................................
Durable goods..................................................
Nondurable goods ...........................................
Transportation and public utilities ......................
Wholesale and retail tra d e .................................
Finance,insurance, and
real e state.........................................................
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 o f unem ploym ent, m onthly data seasonally adjusted
(Numbers in thousands)
Annual average
1995
Weeks of unemployment
Less than 5 weeks ..
5 to 14 weeks ........
15 weeks and o ve r..
15 to 26 weeks ....
27 weeks and over
Mean duration, in weeks ...
Median duration, in weeks
1993
1994
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
3,160
2,522
3,052
1,274
1,778
2,728
2,408
2,860
1,237
1,623
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
2,386
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
2,742
2,348
2,299
1,096
1,203
2,600
2,621
2,319
1,023
1,297
18.1
8.4
18.8
9.2
19.0
9.2
18.9
9.2
18.8
9.5
19.3
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
15.6
7.5
16.5
9.1
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
70
Monthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
September 1995
10.1
2,122
“ Employment and Unemployment Data” in the notes to this section.
8.
Unem ployed persons by reason fo r unem ploym ent, monthly data seasonally adjusted
(Numbers in thousands)
Annual average
1994
1995
Reason for unemployment
1993
Job lo se rs'...............................................................
On temporary layo ff..............................................
Not on temporary layoff .......................................
Job leavers..............................................................
Reentrants ...............................................................
New entrants...........................................................
1994
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Mar.
Apr.
May
4,769
1,104
3,664
946
2,145
874
3,815
977
2,838
791
2,786
604
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
Feb.
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
3,423
1,066
2,357
834
2,526
540
3,615
1,184
2,431
832
2,593
571
54.6
12.6
42.0
10.8
24.6
10.0
47.7
12.2
35.5
9.9
34.8
7.6
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
46.7
14.6
32.2
11.4
34.5
7.4
47.5
15.6
31.9
10.9
34.1
7.5
3.7
.7
1.7
.7
2.9
.6
2.1
.5
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
2.6
.6
1.9
.4
2.7
.6
2.0
.4
June
July
P E R C E N T O F U N E M P LO Y E D
Job losers' ............................................................
On temporary layoff ...........................................
Not on temporary layoff......................................
Job leavers............................................................
Reentrants.............................................................
New entrants ........................................................
PERCENT OF
C IV IL IA N LA B O R FO RC E
Job losers' ...............................................................
Job leavers ..............................................................
Reentrants ...............................................................
New entrants...........................................................
1 Includes persons who completed temporary jobs.
9.
Unem ploym ent rates by sex and age, m onthly data seasonally adjusted
(Civilian workers)
Sex and age
An nual
average
1993
1994
1994
July
Aug.
Sept.
1995
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
Total, 16 years and o v e r....................
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 o v e r..................
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
12.5
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
5.7
11.4
16.7
20.0
14.2
8.5
4.5
4.6
3.9
5.4
11.7
17.6
20.7
15.3
8.5
4.2
4.3
3.4
5.5
11.6
16.1
20.0
13.0
9.1
4.2
4.3
3.5
5.8
11.8
17.5
20.6
15.7
8.7
4.6
4.7
3.8
5.7
11.8
17.6
21.5
14.7
8.6
4.5
4.6
3.8
5.6
11.7
16.4
18.5
15.2
9.0
4.4
4.5
3.8
5.7
12.5
18.2
21.4
15.4
9.3
4.3
4.5
3.9
Men, 16 years and o ver..............................................................
16 to 24 years .............................
16 to 19 years..................................
16 to 17 years.....................................................................
18 to 19 years.....................................................................
20 to 24 years..............................
25 years and o v e r....................................................................
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
6.3
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
5.7
12.0
17.4
20.9
14.5
9.1
4.5
4.6
4.0
5.4
12.1
19.4
22.6
16.7
8.2
4.0
4.2
3.6
5.4
11.7
17.0
20.2
14.6
8.9
4.1
4.2
3.7
5.7
11.8
17.8
21.7
16.1
8.6
4.5
4.5
4.3
5.8
12.3
18.4
22.6
15.2
8.9
4.6
4.7
4.0
5.5
12.0
17.4
18.4
17.4
9.0
4.3
4.3
3.9
5.5
12.5
18.7
21.9
15.9
9.0
4.2
4.3
3.9
Women, 16 years and o ve r.................
16 to 24 years................................
16 to 19 years .........................
16 to 17 years ...................................................................
18 to 19 years ...................................................................
20 to 24 ye ars..........................
25 years and over...................................................................
25 to 54 years .......... .........................................................
55 years and o v e r.....................
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
5.9
11.5
15.9
19.7
13.1
9.1
4.8
5.0
3,
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
5.5
11.2
15.6
18.7
13.7
8.7
4.3
4.5
3.2
5.5
11.5
15.2
19.8
11.3
9.4
4.3
4.4
3.4
5.9
11.9
17.2
19.4
15.2
8.8
4.7
5.0
3.3
5.5
11.4
16.7
20.4
14.0
8.2
4.4
4.6
3.6
5.7
11.3
15.2
18.6
12.8
9.0
4.5
4.7
3.7
5.9
12.6
17.6
21.0
14.9
9.7
4.6
4.6
3.9
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
Monthly Labor Review
September 1995
71
Current Labor Statistics:
10.
Labor Force Data
Unem ploym ent rates by State, seasonally adjusted
June
1994
May
1995
June
1995p
California...................................................
6.0
7.7
66
5.5
8.5
5.9
6.4
5.6
4.1
8.5
6.2
6.7
5.1
4.1
7.6
Florida.......................................................
4.3
55
49
84
6.3
3.9
5.1
43
86
5.1
4.2
5.1
4.2
8.7
5.3
5.2
6.1
5.4
5.1
4.9
4.8
5.1
5.2
5.5
4.7
5.0
5.0
4.8
4.1
4.8
3.7
5.3
5.4
8.1
7.2
3.3
4.7
5.0
7.1
6.3
3.4
4.4
4.9
7.0
6.0
5.1
60
5.6
4.0
6.6
4.7
5.0
5.0
5.7
3.9
6.0
5.1
5.1
5.6
6.2
3.8
6.0
4.8
State
Georgia.....................................................
Idaho.........................................................
Indiana......................................................
low'
Mississippi.................................................
June
1994
May
1995
June
1995p
Montana...................................................
Nebraska..................................................
Nevada ....................................................
New Hampshire ......................................
4.9
2.9
6.1
4.6
5.5
2.6
6.0
3.8
5.5
2.5
5.7
3.6
New Jersey..............................................
New Mexico.............................................
New Y o rk .................................................
North Carolina.........................................
7.0
6.1
7.0
3.9
3.9
6.5
5.7
6.3
4.3
3.3
6.6
5.6
5.9
4.4
3.1
O h io .........................................................
Oklahoma ................................................
Oregon ....................................................
Pennsylvania ...........................................
Rhode Island...........................................
5.6
5.9
5.4
6.0
7.1
4.7
4.7
5.2
5.7
6.4
4.8
4.7
5.2
6.2
6.8
South Carolina ........................................
South Dakota ..........................................
Tennessee ...............................................
Texas .......................................................
U tah.........................................................
6.3
3.2
4.9
6.6
3.7
4.9
2.3
4.6
6.0
3.7
4.7
2.3
4.9
6.3
3.5
Vermont ...................................................
Virginia .....................................................
Washington..............................................
West Virginia ...........................................
Wisconsin.................................................
4.7
4.9
6.5
8.9
4.6
3.9
4.5
6.1
7.7
3.9
4.0
4.4
6.2
7.6
3.3
Wyoming ..................................................
5.3
4.8
4.7
State
p = preliminary
11.
Em ploym ent o f w orkers on nonfarm payrolls by State, seasonally adjusted
(In thousands)
June 1994
State
1
n
a
....
IS
Maryland ......................................................
Minnesota....................................................
Mississippi....................................................
NOTE:
72
May 1995
June 1995p
1,756.2
259.4
1 667 9
1,031.6
12,143.8
1,771.5
262.0
1,753.3
T070.1
12,242.0
1,776.0
261.6
1,754.8
1,070.8
12,256.4
1 750 3
1,544.8
354.9
658 9
5,785.0
1,791.6
1,544.3
359.7
645.2
5,986.0
1,790.3
1,546.7
357.3
642.5
6,002.1
3,256.6
536.7
462.5
5 474 7
2J07.4
3,383.9
534.3
473.9
5,531.7
2756.1
3,396.3
533.6
476.0
5,534.9
2,750.0
1 322 2
1,166.0
1 597 0
1 713 8
530.7
1,349.4
l'l9 6 .4
1,632.7
1 793.9
541.4
1,355.1
1,202.4
1,636.2
1,797.1
542.4
2,148.0
2 895 7
4^137.4
2,315.7
1,058.4
2,465.8
2,159.9
2,948.3
4,258.6
2,362.1
1,055.5
2,540.8
2,162.1
2,953.8
4,241.5
2,369.1
1,052.4
2,542.4
May 1995
Montana.......................................................
Nebraska.....................................................
Nevada .......................................................
New Hampshire..........................................
338.6
793.8
734.5
522.1
350.6
808.6
773.8
532.2
349.3
812.6
777.3
529.9
New Jersey.................................................
New Mexico ................................................
New Y ork.....................................................
North Carolina ............................................
North Dakota ..............................................
3,556.9
655.8
7,809.7
3,359.0
294.0
3,605.0
684.7
7,832.9
3,434.3
301.7
3,603.4
688.1
7,848.3
3,433.6
301.7
Ohio ............................................................
Oklahoma....................................................
Oregon........................................................
Pennsylvania...............................................
Rhode Island ....,..........................................
5,077.1
1,277.3
1,359.9
5,197.1
435.1
5,171.9
1,299.6
1,415.1
5,203.5
432.5
5,169.8
1,302.8
1,419.6
5,204.7
432.7
South Carolina............................................
South Dakota..............................................
Tennessee ..................................................
Texas ..........................................................
Utah ............................................................
1,608.2
332.4
2,421.5
7,727.9
858.8
1,626.1
341.4
2,487.9
7,985.9
902.5
1,632.8
343.3
2,486.4
8,015.8
907.5
Vermont......................................................
Virginia........................................................
Washington .................................................
West Virginia...............................................
Wisconsin....................................................
264.2
3,001.7
2,300.9
672.9
2,478.1
267.7
3,073.4
2,361.7
687.0
2,537.8
267.4
3,080.1
2,368.2
687.5
2,541.8
Wyoming.....................................................
216.1
218.8
217.9
Some data in this table may differ from data published elsewhere because of the continual updating of the database.
Monthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
September 1995
June 1995p
June 1994
State
12.
Em ploym ent o f w orkers on nonfarm payrolls by industry, m onthly data seasonally adjusted
(In thousands)
Annual average
1994
1995
Industry
1993
1994
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
T O T A L ..............................................
P R IV A T E S E C T O R .........................
110,730
91,889
114,034
94,917
114,171
95,061
114,510
95,327
114,762
95,555
114,935
95,740
115,427
96,152
115,624
96,405
115,810
96,588
116,123
96,882
116,302
97,054
116,310
97,049
G O O D S -P R O D U C IN G .......................
M in in g 1 ..................................................
23,352
610
50
350
23,913
600
49
336
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
24,331
583
51
319
24,228
582
51
320
24,235
582
52
320
102
103
103
103
103
104
104
104
105
105
106
105
104
104
104
4,668
1,120
5,010
1,201
5,029
1,199
5,038
1,206
5,077
1,214
5,088
1,222
5,144
1,234
5,166
1,241
5,201
1,250
5,213
1,250
5,256
1,258
5,242
1,255
5,190
1,237
5,231
1,242
5,231
1,236
713
2,836
736
3,073
743
3,087
738
3,094
740
3,123
734
3,132
740
3,170
739
3,186
742
3,209
740
3,223
747
3,251
743
3,244
730
3,223
737
3,252
742
3,253
18,075
12,341
18,303
12,615
18,297
12,610
18,346
12,658
18,355
12,671
18,398
12,709
18,439
12,759
18,472
12,785
18,502
12,813
18,523
12,833
18,525
12,832
18,506
12,818
18,456
12,772
18,422
12,736
18,337
12,653
10,221
6,849
10,431
7,092
10,422
7,088
10,465
7,128
10,481
7,145
10,513
7,175
10,550
7,218
10,574
7,239
10,596
7,259
10,622
7,288
10,633
7,297
10,632
7,296
10,611
7,271
10,594
7,251
10,556
7,218
709
487
517
683
752
502
533
699
755
504
533
700
757
504
534
699
758
504
535
704
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
757
501
542
718
753
497
544
716
750
494
540
712
240
1,339
239
1,387
240
1,390
238
1,396
239
1,397
239
1,405
240
1,412
240
1,421
239
1,428
240
1,435
240
1,439
240
1,442
241
1,439
241
1,432
240
1,431
1,931
363
1,985
351
1,983
352
1,992
350
1,995
348
1,999
345
2,006
344
2,010
342
2,017
341
2,025
340
2,029
336
2,036
337
2,034
336
2,040
337
2,039
336
1,526
1,571
1,570
1,581
1,586
1,589
1,595
1,603
1,608
1,613
1,614
1,616
1,620
1,620
1,625
528
1,756
837
542
896
544
1,749
899
480
863
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
1,766
938
455
846
574
1,761
936
452
846
577
1,754
934
449
845
583
1,734
927
442
842
Metal mining ..............................
Oil and gas extraction ...............
Nonmetallic minerals, except
fu e ls ..........................................
C o n s tru c tio n ......................................
General building contractors......
Heavy construction, except
building.....................................
Special trades contractors........
M a n u fa c tu r in g ....................................
Production workers ..................
D u ra b le 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 p arts......................
Instruments and related products
Miscellaneous manufacturing
industries....................................
May
Junep
116,248 116,498
97,005* 97,229
Ju ly
116,553
97,286
24,146
578
52
316
378
390
392
392
392
394
395
395
396
396
396
394
393
393
389
7,854
5,492
7,872
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
7,874
5,522
7,845
5,501
7,828
5,485
7,781
5,435
1,680
44
675
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
1,694
40
659
1,686
39
651
989
692
1,517
1,081
152
969
691
1,542
1,061
149
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
940
692
1,557
1,051
146
931
690
1,555
1,048
145
920
689
1,561
1,044
145
909
688
1,555
1,039
144
909
117
952
114
953
113
956
113
960
113
965
112
970
112
975
113
982
113
983
112
982
112
981
111
976
110
968
108
963
107
87,378
90,121
90,249
90,529
90,732
90,854
91,252
91,394
91,517
91,799
91,932
91,979
92,020
92,263
92,407
5,829
3,615
248
6,006
3,775
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
6,184
3,919
242
6,177
3,910
240
6,189
3,918
238
6,197
3,930
238
379
1,698
168
740
18
363
410
1,797
169
748
18
392
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
759
17
421
439
1,872
161
758
17
423
441
1,877
159
762
17
424
449
1,881
158
763
16
425
2,214
1,269
2,231
1,305
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
2,267
1,359
2,271
1,365
2,267
1,364
944
927
923
921
921
920
921
920
916
913
910
910
908
906
903
W h o le s a le t r a d e ................................
5,981
6,140
6,138
6,163
6,181
6,195
6,210
6,229
6,251
6,275
6,287
6,300
6,298
6,317
6,334
R e tail t r a d e ..........................................
19,773
20,437
20,459
20,497
20,565
20,580
Building materials and garden
supplies.....................................
General merchandise stores.......
Department stores .....................
Food stores..................................
20,703
20,759
20,760
20,794
20,760
20,762
20,747
20,798
20,852
779
2,488
2,140
3,224
828
2,545
2,212
3,289
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
852
2,539
2,218
3,345
849
2,532
2,213
3,343
849
2,532
2,216
3,353
846
2,530
2,214
3,361
N o n d u ra b le 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.....
S E R V IC E -P R O D U C IN G .....................
T ra n s p o rta tio n an d public
u t ilitie s ..................................................
Transportation..............................
Railroad transportation...............
Local and interurban passenger
transit.........................................
Trucking and warehousing.........
Water transportation...................
Transportation by a ir...................
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
Monthly Labor Review
September 1995
73
Current Labor Statistics:
Labor Force Data
12. Continued— Em ploym ent o f w orkers on nonfarm payrolls by industry, monthly data seasonally adjusted
(In thousands)
1995
1994
Annual average
Industry
Sept.
Dec.
Jan.
Feb.
Mar.
Apr.
May
July
Aug.
2,014
908
1,144
2,123
964
1,134
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
2,205
1,000
1,103
2,205
1,000
1,095
2,206
998
1,096
2,206
999
1,091
828
6,821
890
7,069
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
7,191
945
7,170
944
7,169
947
7,208
947
7,253
2,476
2,560
2,567
2,564
2,587
2,588
2,598
2,600
2,597
2,604
2,603
2,603
2,610
2,607
2,618
6,757
3,238
2,089
1,497
324
455
6,933
3,323
2,075
1,492
308
499
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
6,924
3,305
2,063
1,494
288
473
6,925
3,307
2,060
1,492
285
476
6,934
3,307
2,057
1,491
284
479
6,941
3,310
2,055
1,492
283
484
472
518
522
524
525
525
528
530
530
532
532
528
528
528
527
223
2,197
1,529
231
2,237
1,551
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
2,239
1,536
243
2,237
1,534
243
2,240
1,535
244
2,240
1,536
668
1,322
686
1,373
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
703
1,380
703
1,381
705
1,387
704
1,391
30,197
519
31,488
565
31,573
567
31,693
571
31,789
574
31,888
5/8
32,035
584
32,135
588
32,228
575
32,404
580
32,524
584
32,548
589
32,630 " 32,756
582
577
32,816
588
1,596
1,137
5,735
823
1,906
1,669
1,618
1,139
6,239
855
2,254
2,002
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
1,611
1,152
6,538
866
2,368
2,097
1,615
1,146
6,567
866
2,371
2,096
1,625
1,144
6,593
869
2,377
2,099
1,626
1,143
6,612
871
2,381
2,102
893
950
949
958
967
974
984
991
994
1,006
1,017
1,026
1,039
1,046
1,051
925
349
412
971
334
471
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
580
1,016
341
596
1,021
340
593
1,028
340
601
1,258
1,344
1,361
1,365
1,354
1,364
1,371
1,375
1,380
1,398
1,434
1,462
1,471
1,509
1,521
9,121
9,141
9,168
9,197
9,211
9,223
9,250
9,265
Finance , insurance , a nd real
Security and commodity
Holding and other
Insurance agents, brokers
Hotels and other
Computer and data
Auto repair services,
Amusement and recreation
8,756
9,001
9,011
9,037
9,055
9,074
9,096
1,506
1,541
1,541
1,549
1,548
1,553
1,557
1,562
1,563
1,570
1,576
1,578
1,580
1,585
1,586
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
1,682
3,810
597
932
1,866
2,265
519
631
1,683
3,810
600
930
1,875
2,275
522
634
1,688
3,810
605
928
1,886
2,266
522
635
1,693
3,812
608
928
1,877
2,253
526
635
Offices and clinics of
Nursing and personal
Home health care services........
1,585
3,779
469
924
1,711
2,070
473
567
1,649
3,774
555
927
1,822
2,181
502
602
1,654
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
76
2,035
79
2,059
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
2,057
81
2,060
82
2,060
83
2,065
2,521
2,567
2,575
2,578
2,589
2,595
2,606
2,616
2,634
2,648
2,658
2,674
2,685
2,705
2,714
757
775
778
780
785
785
787
790
793
795
795
799
799
800
803
688
716
716
719
725
731
737
742
752
762
773
785
790
808
808
18,841
2,915
2,128
4,488
1,834
19,118
2,870
2,053
4,562
1,875
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
19,261
2,826
1,987
4,608
1,905
19,243
2,831
1,995
4,602
1,906
19,269
2,831
1,987
4,607
1,916
19,267
2,831
1,985
4,605
1,922
2,654
11,438
6,353
2,687
11,685
6,490
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
2,703
11,827
6,614
2,696
11,810
6,606
2,691
11,831
6,602
2,683
11,831
6,621
5,085
5,195
5,177
5,180
5,201
5,204
5,276
5,211
5,208
5,209
5,208
5,213
5,204
5,229
5,210
Museums and botanical and
Engineering and management
Engineering and architectural
Management and public
Federal, except Postal Service ..
Other State
Other local
1 Includes other industries not shown separately.
= preliminary
NOTE: See notes on the data for a description of the most recent benchmark revision.
p
74
Monthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
JulyP
1994
Miscellaneous retail
Miscellaneous repair services......
June"
1993
Automotive dealers and service
Apparel and accessory stores.....
Furniture and home furnishings
Oct.
Nov.
September 1995
13. Average w eekly hours o f production or nonsupervisory w orkers on private nonfarm payrolls by industry, monthly
data seasonally adjusted
Annual
average
1994
1995
Industry
1993
P R IV A T E S E C T O R ....................................................
1994
34.5
July
34.7
Aug.
34.7
Sept.
34.6
Oct.
34.7
Nov.
34.9
Dec.
34.6
Jan.
34.7
Feb.
34.8
Mar.
34.6
Apr.
34.6
34.5
34.6
40.7
40.6
40.9
40.8
44.7
44.3
44.9
44.9
41.5
4.5
41.4
4.4
41.5
4.2
41.3
4.3
42.8
5.1
40.7
39.8
43.4
44.5
45.1
42.8
42.3
4.9
40.4
38.7
42.5
43.5
45.4
42.0
42.1
4.6
40.3
39.2
42.4
43.8
44.1
42.1
42.3
4.5
40.6
39.4
42.9
43.8
43.7
42.2
41.9
4.6
40.1
39.0
43.0
42.8
42.6
41.9
44.0
41.9
44.7
46.1
41.7
40.2
43.9
41.8
44.5
45.8
41.7
39.9
43.3
41.5
44.3
43.1
41.5
40.1
43.4
41.4
43.4
44.2
41.3
39.8
43.3
41.6
43.8
44.6
41.2
40.0
43.1
41.4
43.2
44.3
41.2
39.4
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
37.0
43.0
40.4
4.0
41.0
40.4
36.9
42.9
40.5
3.9
41.3
40.3
36.9
42.9
40.4
4.0
41.3
40.2
36.6
43.0
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
38.2
43.4
41.2
38.1
38.4
43.2
41.6
38.5
38.1
43.5
41.4
38.3
38.2
43.2
41.1
36.5
32.8
32.9
32.7
32.7
32.9
32.4
32.7
32.9
40.9
41.4
41.4
41.4
41.4
41.4
41.4
41.5
41.6
41.4
41.3
M IN IN G ...............................................................................
44.3
44.7
45.4
44.6
44.9
44.8
44.9
44.7
44.9
44.9
44.6
M A N U F A C T U R IN G ........................................................
41.4
4.1
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
Overtime hou rs.............................................
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
42.8
4.3
5.0
40.8 r 41.2
40.1
40.4
42.7
43.4
43.7
44.7
44.1
44.9
42.1
42.9
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
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
43.6
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
N o n d u ra b le g o o d s ......................................................
Overtime hou rs.............................................
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
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
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
38.6
43.3
42.3
38.0
38.6
43.2
42.2
38.6
38.6
43.2
42.3
38.6
38.7
43.4
42.3
39.0
38.6
43.4
42.3
38.7
32.8
33.0
32.7
D u ra b le g o o d s ...............................................................
34.6
34.2
G O O D S -P R O D U C IN G .....................................................
Overtime h ou rs.............................................
June P JulyP
May
S E R V IC E -P R O D U C IN G .................................................
32.7
32.8
32.8
32.7
T R A N S P O R T A T IO N A N D P U B LIC U T IL IT IE S ...
39.6
39.9
39.9
39.7
40.0
40.0
39.8
39.6
39.8
39.7
39.5
39.8
39.1
39.3
39.7
W H O LE S A LE T R A D E ..................................................
38.2
38.4
38.3
38.2
38.4
38.6
38.4
38.4
38.4
38.4
38.2
38.3
37.9
38.2
38.4
R E T A IL T R A D E ...............................................................
28.8
28.9
29.0
28.9
28.9
29.2
28.9
28.9
29.0
28.8
28.8
29.1
28.7
28.9
28.9
= preliminary
NOTE: See “ Notes on the data” for a description of the most recent benchmark adjustment.
p
14. Average hourly earnings o f production or nonsupervisory w orkers on private nonfarm payrolls by industry
seasonally adjusted
71
An nual
average
1994
1995
Industry
1993
P R IV A T E SE C TO R (In c u rre n t d o lla r s ) .................
G o o d s -p r o d u c in g .............................
12.37
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
JuneP JulyP
12.71
12.83
12.83
12.84
12.89
12.91
12.94
12.94
13.01
13.11
14.72
12.06
11.42
12.06
11.42
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
15.17
14.95
12.28
11.72
15.18
14.99
12.28
11.67
15.29
15.10
12.31
11.71
15.42
15.09
12.42
11.81
10.30
13.62
10.57
13.86
10.57
13.84
11.74
7.29
11.35
10.78
12.05
7.49
11.83
11.05
12.06
7.39
7.41
S e rv ic e -p ro d u c in g ......................................
Transportation and public utilities.............
Wholesale trade .............
Retail trade...........................
Finance, insurance, and real estate ..........
Services........................
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
Aug.
12.72
14.60
14.38
11.74
11.18
= preliminary
July
$10.83 $11.13 $11.13 $11.14 $11.18 $11.25 $11.24 $11.27 $11.29 $11.32 $11.34
$11.40 $11.37 $11.42 $11.49
Mining.............................
Construction ........................
Manufacturing........................
Excluding overtime.............................
P R IV A T E S E C TO R (In co n s ta n t (1 9 8 2 ) do llars )
1994
14.82
12.12
14.90
12.14
13.87
13.88
10.68
14.02
10.71
14.01
10.74
14.03
10.76
14.00
10.79
14.05
10.87
14.15
10.83
14.13
10.87
14.18
10.94
14.22
11.82
11.81
11.90
12.15
7.56
11.99
11.17
12.20
7.60
12.01
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
7.65
12.19
11.34
12.37
7.67
12.32
11.37
12.45
7.72
12.44
11.43
7.39
7.37
7.38
7.40
7.40
7.39
7.39
7.38
7.40
7.36
7.39
7.42
-
NOTE: See “ Notes on the data" for a description of the most recent
benchmark revision.
Monthly Labor Review
September 1995
75
Current Labor Statistics:
Labor Force Data
15. Average hourly earnings o f production or nonsupervisory w orkers on private nonfarm payrolls by
industry
Annual
average
1995
1994
Industry
1993
1994
July
Aug.
Sept.
Oct.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June" July?
P R IV A T E S E C T O R ..........................................................
$10.83 $11.13 $11.05 $11.05 $11.22 $11.28 $11.27 $11.28 $11.36 $11.36 $11.36 $11.41 $11.38 $11.36 $11.41
M IN IN G .................................................................................
14.60
14.89
14.73
14.69
14.92
14.91
14.97
15.09
15.25
15.26
15.24
15.31
15.21
15.24
15.30
14.83
14.67
14.82
14.84
14.88
14.96
14.99
15.09
12.26
12.23
12.24
12.25
12.29
12.28
12.30
12.40
12.83
9.94
9.66
12.23
14.43
17.09
12.03
12.83
9.95
9.67
12.25
14.41
17.03
12.05
12.80
9.98
9.75
12.43
14.72
17.50
12.03
12.83
10.01
9.71
12.31
14.50
17.23
12.07
12.85
10.10
9.79
12.35
14.61
17.38
12.05
12.92
10.20
9.88
12.44
14.65
17.27
12.15
C O N S T R U C T IO N ..............................................................
14.38
14.72
14.75
14.79
14.97
15.05
14.87
M A N U F A C T U R IN G ..........................................................
11.74
12.06
12.04
12.01
12.14
12.10
12.17
Lumber and wood products................................
Furniture and fixtures..........................................
Stone, clay, and glass products.........................
Primary metal industries ......................................
Blast furnaces and basic steel products.........
Fabricated metal products ..................................
12.33
9.61
9.27
11.85
13.99
16.36
11.69
12.67
9.84
9.55
12.13
14.33
16.85
11.93
12.62
9.87
9.54
12.17
14.40
16.93
11.86
12.62
9.87
9.56
12.19
14.34
16.95
11.87
12.76
9.95
9.69
12.27
14.40
17.05
11.99
12.70
9.96
9.70
12.22
14.37
17.08
11.92
12.77
9.93
9.67
12.21
14.44
17.13
12.03
12.87
9.97
9.76
12.21
14.53
17.16
12.09
12.81
9.95
9.67
12.19
14.54
17.30
12.04
Industrial machinery and equipment ...................
Electronic and other electrical equipment .........
Transportation equipment....................................
Motor vehicles and equipment.........................
Instruments and related products......................
Miscellaneous manufacturing..............................
12.73
11.24
15.80
16.10
12.23
9.39
12.99
11.50
16.48
16.98
12.47
9.66
12.94
11.56
16.41
16.89
12.46
9.61
12.92
11.52
16.44
16.92
12.48
9.63
13.04
11.57
16.71
17.27
12.55
9.71
13.03
11.51
16.52
16.98
12.54
9.72
13.11
11.54
16.62
17.11
12.55
9.79
13.19
11.59
16.83
17.37
12.63
9.90
13.15
11.59
16.60
17.12
12.54
9.98
13.15
11.53
16.71
17.26
12.63
9.94
13.15
11.54
16.66
17.23
12.63
9.90
13.05
11.51
16.48
17.03
12.69
9.95
13.15
11.55
16.57
17.13
12.66
9.98
13.15
11.59
16.62
17.17
12.68
9.95
13.21
11.67
16.81
17.47
12.78
10.04
10.98
Food and kindred products................................. 10.45
Tobacco products................................................ 16.89
Textile mill products............................................ 8.88
Apparel and other textile products...................... 7.09
Paper and allied products................................... 13.42
11.25
10.66
19.10
9.13
7.34
13.77
11.28
10.68
20.60
9.12
7.31
13.83
11.20
10.59
18.91
9.12
7.36
13.80
11.31
10.64
18.89
9.20
7.44
13.96
11.30
10.65
18.71
9.19
7.43
13.89
11.35
10.81
19.46
9.26
7.45
13.92
11.42
10.85
18.64
9.31
7.47
13.98
11.44
10.85
18.71
9.35
7.53
14.01
11.43
10.83
19.67
9.31
7.48
14.02
11.45
10.87
20.44
9.30
7.51
14.03
11.58
10.93
20.12
9.36
7.61
14.27
11.52
10.91
21.05
9.35
7.56
14.17
11.55
10.92
21.75
9.39
7.60
14.14
11.69
10.93
22.08
9.39
7.60
14.43
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
12.12
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
19.57
10.77
8.32
12.22
15.53
19.18
10.86
8.19
12.25
15.52
19.15
10.90
8.13
12.37
15.72
19.39
11.02
8.04
T R A N S P O R T A T IO N A N D P U B LIC U T IL IT IE S .....
13.62
13.86
13.81
13.84
13.91
14.01
14.07
14.04
14.08
14.04
14.06
14.14
14.07
14.08
14.19
12.32
12.43
D u ra ble g o o d s .................................................................
N o n d u ra b le g o o d s .........................................................
W H O LE S A LE T R A D E .....................................................
11.74
12.05
12.04
12.00
12.09
12.20
12.15
12.21
12.30
12.28
12.25
12.45
12.32
R E T A IL T R A D E ................................................................
7.29
7.49
7.46
7.44
7.54
7.57
7.57
7.59
7.64
7.63
7.63
7.65
7.65
7.65
7.67
12.24
12.21
12.33
11.34
11.24
11.27
F IN A N C E , IN S U R A N C E , A N D R E A L E S T A T E .....
11.35
11.83
11.72
11.73
11.85
12.02
11.98
12.05
12.17
12.19
12.21
12.32
S E R V IC E S ..........................................................................
10.78
11.05
10.90
10.90
11.11
11.20
11.22
11.29
11.39
11.38
11.36
11.40
= preliminary
NOTE: See “ Notes on the data” for a description of the most recent benchmark revision.
p
76
Nov.
Monthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
September 1995
16.
A verage w eekly earnings o f production or nonsupervisory w orkers on private nonfarm payrolls by industry
Annual average
1994
1995
Industry
1993
1994
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June*1
July"
P R IV A T E S E C TO R
Current dollars................................................... $373.64 $386.21 $386.75 $386.75 $390.46 $394.80 $389.94 $392.54 $390.78 $388.51 $389.65 $391.36 $390.33 $393.06 $398.21
Seasonally adjusted.......................................
386.21 385.44 387.95 392.63 388.90 391.07 392.89 391.67 392.36 394.44 388.85 393.99 397.55
Constant (1982) dollars .................................... 254.87 256.96 256.98 255.79 257.56 260.25 256.54 258.42 256.25 253.93 253.84 253.96 252.80 254.08
M IN IN G .................................................................................
646.78
665.58
661.38
661.05
677.37
673.93
679.64
680.56
683.20
677.54
670.56
678.23
673.80
684.28
680.85
C O N S T R U C T IO N ..............................................................
553.63
572.61
587.05
588.64
598.80
595.98
572.50
573.92
553.06
546.86
565.40
559.49
574.46
593.60
603.60
Current dollars....................................................
Constant (1982) dollars.....................................
486.04
331.54
506.52
337.01
500.86
332.80
504.42
333.61
514.74
339.54
511.83
337.40
517.23
340.28
525.95
346.25
513.66
336.83
510.41
333.60
510.83
332.79
496.52
322.21
508.39
329.27
511.68
330.76
505.92
-
D u ra b le g o o d s .................................................................
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
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
400.20
367.58
525.79
637.38
794.50
484.81
541.43
406.41
375.78
529.33
636.55
759.84
508.15
544.84
412.08
385.73
537.23
642.84
764.72
510.92
533.60
406.98
381.37
538.65
624.09
744.34
499.37
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
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
545.49
462.70
693.81
730.59
513.95
387.06
570.71
477.02
724.11
769.14
521.59
395.21
569.40
482.14
731.28
774.37
523.68
397.01
562.75
474.97
706.02
744.22
520.15
388.55
N o n d u ra b le 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
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
458.57
435.01
774.62
373.46
270.92
603.62
464.26
444.04
844.11
378.68
279.72
606.48
467.78
449.90
904.80
383.11
282.72
606.61
468.77
451.41
867.74
372.78
275.88
616.16
M A N U F A C T U R IN G
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 .............................
456.92
638.74
819.03
468.22
654.05
846.71
464.20
653.40
829.57
469.04
646.93
816.06
479.37
658.14
894.52
475.75
664.02
869.98
477.02
668.17
854.70
481.82
678.48
853.94
466.34
666.82
840.52
466.34
666.14
868.02
470.78
668.12
841.09
460.32
680.68
859.12
464.36
670.90
828.58
463.05
675.12
836.86
468.82
675.96
851.22
441.83
294.52
451.54
308.03
447.20
302.44
448.37
307.64
450.50
310.81
450.92
314.78
455.39
313.95
463.97
314.34
456.60
307.31
451.92
309.32
451.44
309.75
434.03
308.67
451.78
315.32
453.44
314.63
445.21
292.66
T R A N S P O R T A T IO N A N D PU B LIC
U T IL IT IE S ...........................................................................
539.35
553.01
556.54
556.37
557.79
563.20
559.99
555.98
554.75
551.77
549.75
559.94
551.54
556.16
569.02
W H O L E S A L E T R A D E .....................................................
448.47
462.72
462.34
459.60
464.26
472.14
466.56
470.09
469.86
467.87
465.50
476.84
469.39
471.86
478.56
R E T A IL T R A D E ................................................................
209.95
216.46
222.31
220.97
218.66
220.29
217.26
222.39
215.45
214.40
215.93
221.09
219.56
223.38
227.80
F IN A N C E , IN S U R A N C E , A N D R E A L
E S TA T E ..............................................................................
406.33
423.51
418.40
416.42
420.68
435.12
425.29
430.19
441.77
435.18
433.46
447.22
433.30
434.68
448.81
S E R V IC E S ...........................................................................
350.35
359.13
356.43
356.43
359.96
366.24
362.41
365.80
369.04
367.57
365.79
370.50
364.01
365.30
370.78
- 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
Monthly Labor Review
September 1995
77
Current Labor Statistics:
17.
Labor Force Data
Diffusion indexes o f em ploym ent change, seasonally adjusted
(In percent)
Jan.
Time span
and year
Feb.
Mar.
Apr.
May
June
July
Aug.
Oct.
Sept.
Nov.
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
51.3
61.4
58.0
46.2
55.1
63.8
54.6
57.7
60.5
48.6
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
57.9
58.8
67.1
49.3
61.4
66.0
50.0
61.8
66.0
47.2
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
65.9
63.8
70.2
58.8
62.8
70.5
55.8
64.2
69.5
51.7
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
62.4
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
66.0
-
69.4
64.9
“
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
4.1.2
56.5
44.2
51.4
55.0
36.7
46.0
59.0
41.0
50.7
54.0
35.3
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
47.1
46.4
59.0
35.6
46.4
58.6
32.0
50.7
58.3
25.2
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
57.2
56.5
62.9
47.1
56.1
64.4
39.6
55.0
61.5
29.1
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
45.7
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
59.7
-
60.1
56.5
*
59.4
49.6
-
- 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: Em ploym ent status o f the population
(Numbers in thousands)
1986
Employment status
Civilian noninstitutional population........................
Civilian labor force...............................................
Labor force participation
ra te ...................................................................
78
1987
1988
1989
186,393
123,869
189,765
125,303
1992
1993
1994
191,576
126,982
193,550
128,040
196,814
131,056
182,753
119,865
184,613
121,669
65.3
65.6
65.9
66.5
66.4
66.0
66.3
66.2
66.6
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
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
Employed.......................................................
Employment-population ra tio .......................
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
Unemployed ..................................................
Unemployment ra te ....................................
Not in labor fo rc e ................................................
8,237
7.0
62,752
7,425
6.2
62,888
6,701
5.5
62,944
6,528
5.3
62,523
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
188,049
124,787
1991
180,587
117,834
117,342
63.0
3,199
114,142
Monthly Labor Review
1990
September 1995
20. Annual data: Average hours and earnings o f production or nonsupervisory w orkers 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
P riv a te s e c to r.
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)...............................
C o n stru ctio n :
Average weekly hours .....................................................
Average hourly earnings (in dollars)................................
Average weekly earnings (in dollars)...............................
M anufacturin g:
Average weekly hours .....................................................
Average hourly earnings (in dollars)................................
Average weekly earnings (in dollars)...............................
T ra n s p o rta tio n a n d pub lic utilities:
Average weekly hours .....................................................
Average hourly earnings (in dollars)................................
Average weekly earnings (in dollars)...............................
W h o le s a le tra de:
Average weekly h ou rs......................................................
Average hourly earnings (in dollars)............................. .
Average weekly earnings (in dollars)...............................
R e tail tra de:
Average weekly hours .....................................................
Average hourly earnings (in dollars)................................
Average weekly earnings (in dollars)...............................
Finance , Insurance , an d real e state:
Average weekly hours .....................................................
Average hourly earnings (in dollars)................................
Average weekly earnings (in dollars)...............................
S ervices:
Average weekly hours .....................................................
Average hourly earnings (in dollars)................................
Average weekly earnings (in dollars)...............................
19.
Annual data: Em ploym ent levels by industry
(In thousands)
Industry
1986
1987
1988
1989
1990
1991
1992
1993
1994
Total employment....................................................................
Private sector.........................................................................
Goods-producing.................................................................
Mining.............................................................................
Construction ..................................................................
Manufacturing.................................................................
99,344
82,651
24,533
777
4,810
18,947
101,958
84,948
24,674
717
4,958
18,999
105,210
87,824
25,125
713
5,098
19,314
107,895
90,117
25,254
692
5,171
19,391
109,419
91,115
24,905
709
5,120
19,076
108,256
89,854
23,745
689
4,650
18,406
108,604
89,959
23,231
635
4,492
18,104
110,730
91,889
23,352
610
4,668
18,075
114,034
94,917
23,913
600
5,010
18,303
Service-producing................................................................
Transportation and public utilities...................................
Wholesale tra d e ..............................................................
Retail trade .....................................................................
Finance, insurance, and real e sta te ...............................
Services...........................................................................
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
Government...................................................................
Federal......................................................................
State..........................................................................
L o ca l........................ ................................................
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:
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
See "Notes on the data” for a description of the most recent benchmark revision.
Monthly Labor Review
September 1995
79
Current Labor Statistics: Compensation & Industrial Relations
21.
Em ploym ent Cost Index, com pensation,1 by occupation and industry group
(June 1989=100)
1993
1994
1995
Percent change
Senes
June
Sept.
Dec.
Mar.
June
Sept.
Dec.
Mar.
June
3
months
ended
12
months
ended
June 1995
Civilian w o r k e r s 2 ...................................................................................
118.3
119.5
120.2
121.3
122.1
123.3
123.8
124.8
125.6
0.6
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............................................................
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
126.3
127.5
125.7
127.3
124.5
125.8
.6
.4
.4
.6
.7
.6
3.0
2.7
3.4
3.1
2.6
3.0
Workers, by industry division:
Goods-producing..................................................................
Manufacturing.....................................................................
Service-producing.................................................................
Services..............................................................................
Health services................................................................
Hospitals.......................................................................
Educational services.......................................................
Public administration 3 .......................................................
Nonmanufacturing.................................................................
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
126.0
126.9
125.5
127.8
130.2
129.7
127.4
126.1
125.2
.6
.6
.7
.5
.6
.7
.4
.6
.6
2.4
2.8
3.1
2.9
2.8
2.6
3.1
3.2
2.9
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
125.4
125.7
.7
.6
2.8
2.8
P riv a te in d u s try w o r k e r s ................................................................
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...........................................................................
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
126.2
127.0
128.4
125.4
122.4
.7
.6
.5
.4
1.8
3.0
3.0
2.5
3.4
3.0
119.2
120.3
121.2
122.5
123.5
124.5
125.1
126.5
127.3
.6
3.1
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 ....
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
124.4
124.4
124.8
122.4
125.3
.7
.8
.5
.5
1.0
2.6
2.6
2.1
2.8
3.2
Service occupations.........................................................
118.0
118.9
119.5
120.6
121.0
121.8
122.9
123.4
124.0
.5
2.5
Production and nonsupervisory occupations4 ..................
117.9
119.0
119.7
120.7
121.6
122.6
123.1
124.1
125.0
.7
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....................................................................
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
125.9
125.6
127.6
126.7
124.9
127.9
122.0
126.9
128.0
126.6
126.0
128.6
127.7
125.4
.5
.6
.3
.4
.6
.5
.7
.6
.5
.4
.6
.5
.6
.6
2.4
2.5
2.7
2.8
2.2
3.3
1.5
2.8
3.3
3.3
2.3
3.6
3.2
2.1
Service-producing ..............................................................
Excluding sales occupations.....................................
White-collar occupations................................................
Excluding sales occupations ......................................
Blue-collar occupations..................................................
Service occupations......................................................
Transportation and public utilities....................................
Transportation..................................................................
Public utilities..................................................................
Communications...........................................................
Electric, gas, and sanitary services .............................
Wholesale and retail tra d e ...............................................
Excluding sales occupations......................................
Wholesale tra d e .............................................................
Excluding sales occupations....................................
Retail tra d e ....................................................................
Food stores................................................................
General merchandise stores.....................................
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
124.9
125.8
125.6
127.1
123.1
123.6
124.7
123.0
126.8
126.6
127.0
122.8
123.1
124.8
125.1
121.8
120.7
120.7
.8
.6
.8
.6
.8
.5
.6
.6
.6
.2
.9
.9
.6
1.3
.6
.7
-.1
.5
3.1
3.0
3.0
3.0
3.4
2.4
4.1
4.5
3.4
3.7
3.1
2.8
2.8
4.3
4.0
2.2
.1
2.3
See footnotes at end of table.
80
Monthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
September 1995
21. Continued— Em ploym ent Cost Index, com pensation,1 by occupation and industry group
(June 1989=100)
Series
June
Sept.
Dec.
Mar.
June
Percent change
1995
1994
1993
Sept.
Dec.
Mar.
June
3
months
ended
12
months
ended
June 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............................................
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
121.8
124.6
1.3
.7
3.5
3.6
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
119.9
124.4
121.3
126.7
126.7
124.5
125.7
119.4
120.5
124.9
122.1
127.1
127.1
125.4
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
124.1
124.6
128.2
125.3
130.3
129.7
130.3
131.3
.5
.9
.5
.6
.5
.6
1.2
1.5
3.9
3.4
2.6
2.6
2.5
2.0
3.9
4.2
Nonmanufacturing............................................................
White-collar occupations.............................................
Excluding sales occupations........... .........................
Blue-collar occupations...............................................
Service occupations....................................................
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
124.6
125.6
127.1
122.5
123.5
.7
.7
.6
.8
.4
2.8
2.9
2.8
2.9
2.3
S ta te an d local g o v e rn m e n t w o r k e r s ......................................
119.6
121.4
121.9
122.6
123.1
125.0
125.6
126.4
126.9
.4
3.1
Workers, by occupational group:
White-collar workers.........................................................
Professional specialty and technical.............................
Executive, administrative, and managerial....................
Administrative support, including clerical.......................
Blue-collar workers...........................................................
119.6
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
126.6
126.3
127.4
126.9
126.3
.3
.2
.4
.5
.7
3.0
2.9
3.2
2.9
2.9
Workers, by industry division:
Services............................................................................
Services excluding schools5 ..........................................
Health services............................................................
Hospitals....................................................................
Educational services....................................................
Schools.....................................................................
Elementary and secondary ....................................
Colleges and universities.......................................
Public administration3 .......................................................
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
127.1
127.7
129.8
129.9
126.8
127.1
127.4
126.1
126.1
.3
1.0
1.1
1.2
.2
.2
.2
.1
.6
3.0
3.6
3.7
4.3
3.0
3.0
2.9
3.4
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.
Monthly Labor Review
September 1995
81
Current Labor Statistics: Compensation & Industrial Relations
22.
Em ploym ent Cost Index, w ages and salaries, by occupation and industry group
(June 1989=100)
1993
1994
1995
Percent change
Series
June
Sept.
Dec.
Mar.
June
Sept.
Dec.
Mar.
June
3
months
ended
12
months
ended
June 1995
C ivilian w o rk e rs 1 ...................................................................................
115.2
116.4
117.1
117.8
118.6
119.8
120.4
121.3
122.2
0.7
3.0
Workers, by occupational group:
White-collar w orkers...........................................................
Professional specialty and technical................................
Executive, administrative, and managerial.......................
Administrative support, including clerical ........................
Blue-collar workers..............................................................
Sendee occupations............................................................
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
123.1
124.7
122.8
123.4
120.3
121.8
.6
.4
.5
.5
.9
.5
2.8
2.8
3.2
3.0
3.1
3.1
Workers, by industry division:
Goods-producing...................................................................
Manufacturing.....................................................................
Service-producing.................................................................
Services............................................................................
Health services..............................................................
H ospitals.....................................................................
Educational services ......................................................
Public administration 2 ......................................................
Nonmanufacturing...............................................................
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
121.4
122.9
122.5
124.8
126.6
126.0
125.1
122.3
121.9
.7
.8
.7
.3
.4
.4
.1
.3
.7
2.9
3.3
3.0
2.9
2.6
2.4
3.1
3.2
2.9
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
121.5
121.8
.7
.7
2.9
3.0
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
122.7
123.4
124.4
.8
.5
.6
2.8
2.9
2.6
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
122.5
119.3
.5
2.1
3.1
2.7
116.1
117.1
118.0
119.0
119.9
120.9
121.6
122.9
123.5
.5
3.0
Blue-collar w orkers........................................................
Precision production, craft, and repair
occupations...............................................................
Machine operators, assemblers, and inspectors........
Transportation and material moving occupations.......
Handlers, equipment cleaners, helpers, and
laborers......................................................................
113.2
114.1
114.8
115.6
116.5
117.5
118.0
119.0
120.1
.9
3.1
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
119.9
120.9
117.8
.9
1.1
.7
2.9
3.2
3.3
114.3
114.9
115.7
116.6
117.3
117.9
118.9
120.1
121.2
.9
3.3
Service occupations.......................................................
114.1
114.9
115.3
116.3
116.8
117.6
118.8
119.4
120.0
.5
2.7
Production and nonsupervisory occupations3 ...............
114.2
115.3
115.9
116.6
117.5
118.5
119.1
119.9
121.0
.9
3.0
Workers, by industry division:
Goods-producing.............................................................
Excluding sales occupations.....................................
White-collar occupations..............................................
Excluding sales occupations.....................................
Blue-collar occupations................................................
Service occupations.....................................................
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
121.4
120.9
123.8
122.5
119.9
121.9
.8
.8
.7
.6
.9
1.1
2.9
3.0
2.9
3.1
2.8
3.6
Construction ...................................................................
110.4
111.3
111.1
112.2
113.6
114.6
114.7
114.8
115.7
.8
1.8
Manufacturing.................................................................
White-collar occupations..........................................
Excluding sales occupations..................................
Blue-collar occupations............................................
Service occupations..................................................
Durables......................................................................
Nondurables.................................................................
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
121.9
123.9
122.4
120.4
121.5
121.9
121.9
122.9
124.7
123.2
121.6
122.8
122.9
122.9
.8
.6
.7
1.0
1.1
.8
.8
3.3
3.4
3.4
3.2
3.9
3.5
2.8
Service-producing............................................................
Excluding sales occupations.....................................
White-collar occupations..............................................
Excluding sales occupations...................................
Blue-collar occupations................................................
Service occupations.....................................................
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
121.6
122.5
122.3
123.8
120.3
119.8
.7
.6
.8
.5
.9
.4
2.9
2.9
2.9
2.8
3.5
2.7
Transportation and public utilities...............................
Transportation............................................................
Public utilities..............................................................
Communications......................................................
Electric, gas, and sanitary services........................
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
122.0
119.8
124.5
124.6
124.4
.7
.7
.5
.2
.8
4.1
4.4
3.7
4.3
2.9
P riv a te in d u s try w o r k e r s .............................................................
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........................................................................
See footnotes at end of table.
82
Monthly Labor Review
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Federal Reserve Bank of St. Louis
September 1995
22. Continued— Em ploym ent Cost Index, w ages and salaries, by occupation and industry group
(June 1989=100)
Percent change
1995
1994
1993
Series
June
Sept.
Mar.
Dec.
Sept.
June
Dec.
Mar.
June
3
months
ended
12
months
ended
June 1995
Wholesale and retail trade..........................................
Excluding sales occupations......... ........................
Wholesale tra d e .......................................................
Excluding sales occupations................................
Retail trade................................................................
Food stores............................................................
General merchandise stores..................................
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
120.6
120.9
122.7
122.9
119.6
117.6
118.6
1.0
.6
1.5
.6
.8
-.2
.6
2.7
2.6
3.7
3.5
2.2
-.2
1.9
Finance, insurance, and real estate...........................
Excluding sales occupations................................
Banking, savings and loan, and other
credit agencies.......................................................
Insurance..................................................................
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
117.0
120.2
1.7
.8
3.4
3.6
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
119.7
120.8
.4
.8
4.1
3.4
Services.......................................................................
Business services......................................................
Health services..........................................................
Hospitals..................................................................
Educational services..................................................
Colleges and universities........................................
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
124.4
122.9
126.7
125.9
125.9
125.9
.4
.7
.4
.4
.2
.3
2.6
2.9
2.6
2.1
3.0
3.0
Nonmanufacturing..........................................................
White-collar occupations.............................................
Excluding sales occupations........... .........................
Blue-collar occupations...............................................
Service occupations....................................................
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
120.9
122.1
123.5
118.5
119.8
.8
.8
.5
.9
.5
2.7
2.7
2.7
3.0
2.7
S ta te a n d local g o v e rn m e n t w o r k e r s ....................................
117.4
119.3
119.7
120.4
120.7
122.8
123.4
124.3
124.6
.2
3.2
Workers, by occupational group:
White-collar workers......................................................
Professional specialty and technical..........................
Executive, administrative, and managerial..................
Administrative support, including clerical....................
Blue-collar workers........................................................
117.6
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
124.6
125.0
124.3
122.9
123.8
.2
.2
.2
.3
.6
3.1
3.1
3.3
2.9
3.1
Workers, by industry division:
Services .........................................................................
Services excluding schools4 .......................................
Health services.........................................................
Hospitals.................................................................
Educational services....................................................
Schools.....................................................................
Elementary and secondary ....................................
Colleges and universities.......................................
Public administration 2 ....................................................
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
125.1
125.5
126.6
126.3
124.9
125.1
125.8
122.9
122.3
.2
.4
.5
.4
.1
.1
.2
-.2
.3
3.1
3.0
3.0
3.5
3.1
3.2
3.3
3.1
3.2
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.
Em ploym ent Cost Index, benefits, private industry w orkers by occupation and industry group
(June 1989 = 100)
1993
1994
1995
Percent change
Series
June
Sept.
Dec.
Mar.
June
Sept.
Dec.
Mar.
June
3
months
ended
12
months
ended
June 1995
P riv a te In d u s try w o r k e r s ..................................................................
126.7
127.7
128.3
130.7
131.7
132.8
133.0
134.5
135.1
0.4
2.6
Workers, by occupational group:
White-collar workers ...........................................................
Blue-collar workers..............................................................
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
136.0
133.6
.6
.2
3.3
1.6
Workers, by industry group:
Goods-producing.................................................................
Service-producing................................................................
Manufacturing.....................................................................
Nonmanufacturing...............................................................
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
135.9
134.1
135.2
134.7
.0
.7
-.1
.6
1.5
3.4
1.7
3.0
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
Monthly Labor Review
September 1995
83
Current Labor Statistics: Compensation & Industrial Relations
24.
Em ploym ent Cost Index, private nonfarm w orkers, by bargaining status, region, and area size
(June 1989=100)
1993
1994
1995
Percent change
Series
June
Sept.
Dec.
Mar.
June
Sept.
Dec.
Mar.
June
3
months
ended
12
months
ended
June 1995
C O M P E N S A TIO N
W o rk e rs , b y barga ining s ta tu s 1
Union .....................................................................................
Goods-producing.................................................................
Service-producing................................................................
Manufacturing.....................................................................
Nonmanufacturing...............................................................
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
125.8
125.9
125.6
126.6
125.0
0.6
.6
.6
.2
.8
2.3
1.7
3.1
1.4
2.9
Nonunion................................................................................
Goods-producing.................................................................
Service-producing................................................................
Manufacturing.....................................................................
Nonmanufacturing...............................................................
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
125.2
125.9
124.8
126.9
124.5
.7
.6
.8
.6
.7
2.9
2.7
3.1
3.3
2.8
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
126.6
124.3
126.9
123.4
.8
.5
.9
.7
3.1
2.9
2.7
2.4
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
125.4
125.3
.7
.4
2.9
2.3
Union .....................................................................................
Goods-producing.................................................................
Service-producing................................................................
Manufacturing.....................................................................
Nonmanufacturing...............................................................
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
119.9
120.6
119.3
122.3
120.5
120.6
.7
.8
.6
.6
.7
2.6
2.2
3.0
2.3
2.8
Nonunion................................................................................
Goods-producing.................................................................
Service-producing................................................................
Manufacturing.....................................................................
Nonmanufacturing...............................................................
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
121.8
122.2
121.5
123.8
121.0
.8
.7
.8
.9
.8
3.0
3.0
2.9
3.6
2.7
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
122.1
120.8
122.2
120.9
.7
.7
1.1
.8
2.8
2.9
3.3
2.5
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
121.6
121.3
.8
.7
3.0
2.7
W o rk e rs , by re g io n 1
Northeast................................................................................
South .....................................................................................
Midwest (formerly North Central)..........................................
W est.......................................................................................
W o rk e rs , b y a re a size 1
Metropolitan areas.................................................................
Other areas............................................................................
W A G E S A N D S A L A R IE S
W o rk e rs , b y barga ining sta tu s 1
W o rk e rs , b y reg io n 1
Northeast................................................................................
South .....................................................................................
Midwest (formerly North Central)..........................................
W est.......................................................................................
W o rk e rs , b y a re a s iz e 1
Metropolitan areas.................................................................
Other areas............................................................................
1 The indexes are calculated differently from those for the occupation and
industry groups. For a detailed description of the index calculation, see the
84
Monthly Labor Review
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Federal Reserve Bank of St. Louis
September 1995
M o n th ly L a b o r R e v ie w Technical
Employment Cost Index,” May 1982.
Note,
"Estimation
procedures for the
25. Percent o f full-tim e em ployees participating in em ployer-provided benefit plans, 1980-91
Small
private
establish
ments2
Medium and large private establishments'
Item
Time-off plans
Participants with:
Paid lunch time ...............................................
Average minutes per day..............................
Paid rest tim e ..................................................
Average minutes per day..............................
Paid funeral leave...........................................
Average days per occurrence......................
Paid holidays ...................................................
Average days per year.................................
Paid personal leave.........................................
Average days per year.................................
Paid vacations.................................................
Paid sick leave................................................
Unpaid maternity leave ...................................
Unpaid paternity leave ....................................
Insurance plans
Participants in medical care plans.....................
Participants with coverage for
Home health c a re .........................................
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................................... ..........................
Retirement plans
Participants in defined benefit pension plans*....
Participants with:
Early retirement available .............................
Ad hoc pension increase in last 5 years......
Terminal earnings formula.......................
Benefit coordinated with Social Security......
Participants in defined contribution plans..........
Participants in plans with tax-deferred savings
arrangements ...............................................
Other benefits
Employees eligible for:
Flexible benefits plans ...................................
Reimbursement accounts...............................
1983
1980 1981
1982
75
99
10.1
20
100
62
10
75
99
10.2
23
99
65
9
25
76
25
"
99
10.0
24
3.8
99
67
_
-
-
_
-
97
97
96
10
-
11
25
74
25
99
9.8
25
3.7
100
67
1985
1988
1986
1989
1991
1990
1990
1987
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
98
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
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
96
95
90
92
66
70
99
70
66
76
79
98
80
74
75
80
97
97
96
9
26
73
26
99
9.8
23
3.6
99
67
83
69
93
93
58
98
-
60
99
-
62
99
50
37
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
47
51
43
36
36
27
33
- $10.13 $11.93 $12.05 $12.80 $19.29 $25.31 $26.60
64
66
69
63
58
56
54
51
- $32.51 $35.93 $38.33 $41.40 $60.07 $72.10 $96.97
42
$25.13
67
$109.34
35
$15.74
71
$71.89
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
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
84
84
84
82
82
80
76
63
63
59
20
93
90
55
98
7
56
54
48
54
95
7
58
49
31
92
90
33
100
18
9
89
88
16
100
8
9
97
-
-
55
98
53
45
-
56
98
50
43
-
-
-
~
“
58
97
52
45
-
“
37
58
99
53
43
64
97
51
54
55
-
“
' 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
1984
State and local
governments3
46
62
99
61
52
63
97
47
54
56
- .
56
67
99
68
61
38
$25.53
65
$117.59
67
97
41
57
61
7 53
64
98
35
57
62
7 60
59
98
26
55
62
45
62
97
22
64
63
48
26
33
36
41
44
17
28
45
2
5
5
12
9
23
10
36
1
8
5
31
“
to the average monthly employee contribution for family coverage, which
includes the employee.
6 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.
Monthly Labor Review
September 1995
85
Current Labor Statistics: Compensation & Industrial Relations
26. Specified com pensation and w age rate changes from contract settlem ents, and w age rate changes under all
agreem ents, private industry collective bargaining agreem ents covering 1,000 w orkers or m ore
(In percent)
Annual average
Quarterly average
Measure
1993
1993
1994
1995
1994
III
IV
I
II
III
IV
I
IP
R a te c h a n g es u n d er s ettlem en ts:
S p e c ifie d to ta l compensation changes,
settlements covering 5,000 workers or more:
First year of contract......................................
Annual average over life of contract...................
3.0
2.4
2.3
2.4
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
1.7
1.8
1.8
Specified wage changes, settlements covering
1,000 workers or more:
First year of contract...........................................
Annual average over life of contract..............
2.3
2.1
2.0
2.3
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
2.1
2.1
2.2
3.0
2.7
.8
.7
.4
.8
.9
.6
3
.9
1.9
.2
.6
1.9
.2
.1
.6
.0
.5
.2
(2)
.1
.3
i2)
.2
.6
(2)
.1
.7
.1
2
.3
.1
1
.2
.0
W a g e ra te c h a n g es u n d e r all a g ree m e nts :
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.
86
Monthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
September 1995
p
= preliminary.
8
2
.5
.1
27. Specified com pensation and w age rate changes from contract settlem ents, and w age rate changes under all
agreem ents, private industry collective bargaining agreem ents covering 1,000 w orkers or m ore during 4-quarter
periods
(In percent)
_________________ _______
Average for four quarters ending-
IP
I
IV
III
II
I
IV
III
1995
1994
1993
Measure
R a te c h a n g e s u n d e r settlem en ts:
Specified total compensation changes, settlements covering
5,000 workers or more, all industries:
First year of contract...........................................................................
Annual average over life of contract..................................................
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
1.2
1.7
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 b o th .........................
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 b oth .........................
Contracts with neither lump sums nor COLA................................
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
2.2
1.5
2.3
2.4
2.2
2.2
2.3
1.8
1.7
1.8
1.6
1.8
2.2
1.8
2.2
1.8
2.3
Manufacturing:
First year of contract........................................................................
Contracts with COLA clauses .......................................................
Contracts without COLA clauses...................................................
Contracts with either lump sums, COLA, or b oth .........................
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 b o th .........................
Contracts with neither lump sums nor COLA................................
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
2.0
2.1
2.3
Nonmanufacturing:
First year of contract....................................... ................................
Contracts with COLA clauses ........................................................
Contracts without COLA clauses...................................................
Contracts with either lump sums, COLA, or b oth .........................
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 b oth .........................
Contracts with neither lump sums nor COLA................................
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
2.8
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
2.6
2.3
2.4
2.3
1.6
2.2
1.5
2.3
1.4
2.3
2.6
2.3
2.4
2.3
Construction:
First year of contract........................................................................
Annual average over life of contract................................................
2.0
2.4
2.1
2.6
2.4
2.7
1.7
2.5
1.8
2.6
1.8
2.5
1.5
2.4
2.3
2.7
2.6
3.0
2.9
2.7
2.9
2.7
2.6
2.6
.9
1.7
.2
.8
1.9
.2
.6
1.9
.2
.5
1.9
.3
.5
1.8
.3
W a g e ra te ch a n g e s u n d e r all a g ree m e n ts :
Average wage change2 .........................................................................
Source:
Current settlements.............................................................................
Prior settlements............................................................. ....................
COLA provisions..................................................................................
.6
1.8
.3
.9
1.9
.2
.9
1.8
.2
1.9
(1)
(1)
1.7
2.2
2.0
0
(1)
1.7
2.3
1.7
(')
(1)
1.5
1.8
2.2
0
0
1.9
2.3
1 Data do not meet publication standards.
2 Because of rounding, total may not equal sum of parts.
p = preliminary.
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Federal Reserve Bank of St. Louis
Monthly Labor Review
September 1995
87
Current Labor Statistics: Compensation & Industrial Relations
28. Specified changes in the cost o f com pensation and com ponents annualized o ver the life o f the contract in
private industry collective bargaining settlem ents covering 5,000 w orkers or m ore, by quarter, and during 4-quarter
periods
(In percent)
1993
Measure
III
1994
IV
I
II
1995
III
IV
I
II
1.2
1.5
1.5
.6
1.1
1.2
1.0
.9
1.1
1.1
1.1
1.1
Quarterly average
All industries:
Compensation................................................................
Cash payments................................................................
W ages.........................................................................................
Benefits..............................................................................
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
0.8
.9
.9
.5
Average for four quarters
All industries:
Compensation......................................................................
Cash payments........................................................................
W ages....................................................................................
Benefits....................................................................
With contingent pay provisions:
Compensation................................................................
Cash payments...................................................................
W ages.......................................................................
Benefits.......................................................................
Without contingent pay provisions:
Compensation............................................................
Cash payments..................................................................
W ages............................................................................
Benefits.................................................................................
88
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
1.1
1.2
1.1
.8
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
1.4
1.5
1.3
1.1
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
1.0
1.1
1.1
.8
Manufacturing:
Compensation...................................................................................
Cash payments...................................................................
W ages................................................................................
Benefits...................................................................
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
1.2
1.3
1.2
1.0
Nonmanufacturing:
Compensation.................................................................
Cash payments............................................................................
W ages..............................................................................................
Benefits......................................................................................
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
1.0
1.1
1.1
.8
Goods-producing:
Compensation..................................................................
Cash payments......................................................................
W ages.............................................................................................
Benefits...................................................................................
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
1.3
1.4
1.3
1.2
Service-producing:
Compensation.................................................................................
Cash payments...........................................................
W ages.....................................................................
Benefits................................................................................
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
1.7
.8
1.0
1.0
.4
Monthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
September 1995
29. Specified com pensation and w age rate changes from contract settlem ents, and w age rate changes under all agreem ents,
State and local governm ent collective bargaining agreem ents covering 1,000 w orkers o r m ore (in percent)___________________
Annual average
Measure
1992
1993
1994
0.6
1.9
0.9
1.8
2.8
3.1
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)
Changes under settlements:
Total compensation ' changes,2 settlements covering 5,000 workers or more:
Wage changes, settlements covering 1,000 workers or more:
Wage changes under all agreements:
Source:
' 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.
* Less than 0.05 percent.
30. W ork stoppages involving 1,000 w orkers or more
1993
1994
Number of stoppages:
Days idle:
Percent of estimated working
time1 ..........................................
Sept.
Aug.
July
JuneP
MayP
Apr.P
45
45
4
9
5
11
7
14
4
9
1
6
0
4
1
4
1
4
4
7
2
1
2
3
18.2
322.2
14.3
58.6
32.0
8.0
2.6
.0
37.7
3.0
17.6
32.0
14.0
2.0
18.4
322.2
33.1
88.2
59.4
32.7
26.8
17.2
52.9
18.2
32.8
56.9
28.2
13.0
3,981.0
5,020.5
436.1
678.5
638.5
505.9
420.8
342.2
368.5
306.8
367.8
529.7
336.2
262.0
.01
.02
.02
.02
.02
.02
.02
.02
.02
.01
.01
.01
.02
.01
1 Agricultural and government employees are included in the total employed and
total working time: private household, forestry, and fishery employees are excluded.
An explanation of the measurement of idleness as a percentage of the total time
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
Feb.P
Jan.p
Dec.
Nov.
Oct.
Mar.P
35
36
Workers involved:
Beginning in period (in
In effect during period (in
1995
1994
Annual totals
Measure
worked is found in “ Total economy' measure of strike idleness,”
view, October 1968, pp. 54-56.
p = preliminary.
Monthly Labor Review
M o n th ly L a b o r R e
September 1995
89
Current Labor Statistics: Price Data
31. Consum er Price Indexes fo r All Urban Consum ers and fo r Urban W age Earners and Clerical W orkers: U.S. city
average, by expenditure categ ory and com m odity o r service group
(1982-84=100, unless otherwise indicated)
Annual
Series
1994
1995
*
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
148.2
444.0
148.4
444.4
149.0
446.4
149.4
447.5
149.5
448.0
149.7
448.6
149.7
448.4
150.3
450.3
150.9
452.0
151.4
453.5
151.9
455.0
152.2
455.8
152.5
456.7
152.5
457.0
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
144.8
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
148.4
147.9
148.1
167.5
137.1
132.2
177.5
140.6
137.3
136.4
131.5
151.2
148.8
154.0
148.6
148.1
148.2
168.2
137.3
132.9
176.7
140.7
138.1
138.0
130.8
151.4
149.1
153.8
Housing......................................................................................
S helter..............................................................................
Renters’ costs (12/82=100)...................................................
Rent, residential.....................................................................
Other renters’ c o s ts ...............................................................
Homeowners’ costs (12/82=100)...........................................
Owners’ equivalent rent (1 2/8 2=1 0 0 )..................................
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 g a s ...............................................
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
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
148.5
165.5
174.7
157.5
206.6
170.6
170.9
158.1
135.0
139.4
129.0
125.0
113.8
87.9
121.9
152.7
122.5
110.7
136.4
143.1
149.2
166.4
176.7
157.9
213.5
171.2
171.4
158.3
135.1
139.8
128.7
125.1
113.7
87.1
121.9
153.0
123.0
111.1
137.4
143.6
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
131.0
127.5
132.6
127.1
125.9
145.6
151.7
133.4
130.4
126.4
130.9
128.1
126.0
149.5
155.4
130.9
127.6
124.9
125.7
129.2
125.0
150.6
155.7
131.1
127.8
125.7
125.5
128.6
124.5
152.4
155.9
134.2
131.2
128.4
131.1
129.5
125.1
152.3
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
126.0
124.0
123.0
129.0
124.0
150.1
157.0
131.1
127.7
125.6
125.9
126.8
124.8
150.4
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
130.5
127.1
125.5
124.4
121.6
124.6
153.6
156.9
128.3
124.8
123.4
121.1
123.0
123.3
151.8
157.2
Transportation ................................................................................
Private transportation..................................................................
New vehicles.............................................................................
New cars.................................................................................
Used c a rs ..................................................................................
Motor fuel ..................................................................................
Gasoline.................................................................................
Maintenance and repair............................................................
Other private transportation.....................................................
Other private transportation commodities.............................
Other private transportation services....................................
Public transportation...................................................................
130.4
127.5
132.7
131.5
133.9
98.0
97.7
145.9
156.8
103.4
169.1
167.0
134.3
131.4
137.6
136.0
141.7
98.5
98.2
150.2
162.1
103.5
175.8
172.0
134.6
131.8
137.4
135.8
142.6
100.5
100.4
150.0
161.5
103.3
175.1
171.4
135.9
133.0
137.3
135.6
144.0
104.1
104.1
150.7
162.0
103.3
175.7
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
134.9
140.1
138.5
151.5
100.4
100.2
151.9
167.6
104.3
182.4
165.6
137.3
134.9
140.6
139.0
152.4
98.7
98.4
152.0
168.8
104.2
184.0
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
135.2
140.7
139.0
154.8
97.5
97.2
152.7
170.2
104.6
185.6
174.5
139.1
136.2
141.1
139.3
156.7
99.5
99.3
153.2
170.9
104.5
186.5
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
141.1
137.9
141.0
139.1
158.3
106.1
106.3
153.6
169.9
104.6
185.2
182.5
140.1
136.9
140.3
138.3
157.5
103.6
103.7
154.0
169.6
104.8
184.8
181.8
Medical c a re ..............................................................................
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
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
219.8
203.8
223.5
200.8
255.9
220.8
204.4
224.6
201.6
257.6
Entertainment.................................................................................
Entertainment commodities........................................................
Entertainment services................................................................
145.8
133.4
160.8
150.1
136.1
166.8
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
153.2
138.1
171.2
153.6
138.5
171.4
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
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
205.3
226.4
146.7
142.8
151.0
232.5
212.7
234.2
205.7
226.2
146.9
142.7
151.4
233.3
212.9
235.1
1993
1994
144.5
432.7
Food and beverages.....................................................................
Food.............................................................................................
Food at hom e ...........................................................................
Cereals and bakery products.................................................
Meats, poultry, fish, and eggs................................................
Dairy products........................................................................
Fruits and vegetables.............................................................
Other foods at home..............................................................
Sugar and sweets................................................................
Fats and o ils ........................................................................
Nonalcoholic beverages......................................................
Other prepared foods..........................................................
Food away from home ............................................................
Alcoholic beverages....................................................................
C O N S U M E R PR IC E IN D E X FO R A L L U R B A N C O NS UM ER S:
All ite m s....................................................................................
All items (1967-100) .....................................................................
S ee footnotes at end of table.
90
Monthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
September 1995
31. Continued— Consum er Price Indexes fo r All Urban Consum ers and fo r Urban W age Earners and Clerical W orkers: U.S. city
average, by expenditure category and com m odity or service group
(1982-84=100, unless otherwise indicated)
Series
1995
1994
Annual
average
July
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
149.4
134.8
145.6
128.1
130.3
131.2
132.8
125.1
149.5
134.9
145.6
128.3
130.2
132.3
132.2
125.7
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
152.5
136.6
148.4
129.4
130.4
127.1
135.1
128.0
152.5
136.2
148.6
128.5
129.1
124.8
134.3
127.8
164.2
168.2
138.0
168.9
214.7
185.8
164.4
168.2
137.9
168.8
215.4
187.8
164.6
168.6
136.3
169.5
216.8
188.5
164.7
168.6
135.8
170.5
217.5
189.0
164.7
168.3
135.9
171.1
218.2
188.9
165.9
169.4
137.2
172.6
219.8
189.7
166.7
170.4
137.0
173.4
221.3
190.9
167.3
171.2
136.9
175.0
221.8
191.1
167.5
171.3
136.7
176.1
222.4
191.4
167.7
171.5
137.1
175.9
223.0
191.7
168.6
172.2
139.5
176.8
223.5
191.5
169.2
173.2
139.7
176.5
224.6
192.1
149.1
144.9
149.8
144.8
127.8
129.4
132.4
136.6
171.0
158.7
106.8
154.0
156.4
136.8
99.2
167.7
149.8
145.5
150.4
145.5
128.4
130.4
133’.7
137.4
171.7
159.4
108.5
154.6
157.0
136.8
102.4
168.5
150.2
146.0
150.6
145.8
129.0
131.4
133.7
138.1
172.2
159.6
108.2
155.0
157.5
137.7
102.0
168.8
150.4
146.1
150.7
145.9
129.3
131.4
133.2
138.1
172.2
159.7
105.8
155.5
158.0
138.3
100.4
169.3
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
152.1
147.7
152.7
147.6
129.5
130.5
132.4
138.7
175.1
162.2
103.2
157.8
160.4
139.4
96.7
172.4
152.5
148.3
153.2
148.1
130.1
131.3
133.3
139.6
175.5
162.4
103.9
158.3
160.7
139.7
98.4
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
153.3
148.8
153.7
148.7
130.4
131.7
136.0
139.6
176.9
163.5
109.3
158.3
160.9
138.9
104.3
173.4
153.4
148.6
153.7
148.7
129.5
130.5
135.3
139.0
177.3
164.1
108.1
158.5
161.1
138.3
101.9
174.1
67.5
22.5
67.4
22.5
67.1
22.4
66.9
22.3
66.9
22.3
66.8
22.3
66.8
22.3
66.5
22.2
66.3
22.1
66.0
22.0
65.8
22.0
65.7
21.9
65.6
21.9
65.6
21.9
142.1
423.1
145.6
433.8
145.8
434.3
146.5
436.4
146.9
437.5
147.0
437.8
147.3
438.6
147.2
438.6
147.8
440.2
148.3
441.7
148.7
443.0
149.3
444.6
149.6
445.6
149.9
446.5
149.9
446.5
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
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
147.8
147.4
147.2
167.3
136.6
131.9
176.7
140.2
137.3
136.3
130.7
151.0
148.7
153.4
148.0
147.6
147.4
167.9
137.0
132.5
176.1
140.3
138.0
137.9
130.0
151.1
149.0
153.1
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
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
87.6
116.7
150.9
119.E
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
145.5
160.9
152.6
157.2
206.2
155.6
155.8
145.2
134.4
142.4
123.8
124.6
113.1
87.8
121.1
153.2
121.3
109.5
136.7
146.1
146.1
161.7
153.9
157.5
213.7
156.1
156.3
145.4
134.7
142.9
124.0
124.6
113.1
87.0
121.2
153.4
121.8
109.9
137.6
146.6
July
Aug.
148.2
133.8
144.9
126.9
128.4
130.4
130.3
124.8
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
157.9
162.0
134.2
162.9
202.9
177.0
163.1
167.0
136.3
168.6
213.4
185.4
163.4
167.3
137.9
168.1
213.8
184.7
Special indexes:
All items less fo o d ......................................................................
All items less shelter...................................................................
All items less homeowners’ costs (12/82—100)........................
All items less medical ca re .........................................................
Commodities less fo o d ................................................................
Nondurables less food ........................ .......................................
Nondurables less food and apparel ...........................................
Nondurables.................................................................................
Services less rent o f shelter (12/82=100)...............................
Services less medical ca re .........................................................
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
Purchasing power of the consumer dollar:
1982-84—$1.00...........................................................................
1967 -$ 1.00 .................................................................................
69.2
23.1
1993
1994
Food and beverages....................................................................
Commodities less food and beverages.......................................
Nondurables less food and beverages ....................................
Apparel commodities..............................................................
Nondurables less food, beverages, and apparel ..................
Durables....................................................................................
144.5
131.5
141.6
125.3
128.1
131.0
129.6
121.3
Rent of shelter (12/8 2=1 0 0 )......................................................
Household services less rent o f shelter (12/82=100).............
Transportation services...............................................................
Medical care services..................................................................
Other services.............................................................................
Sept.
June
C O N S U M E R P R IC E IN D E X FO R U R B A N W A G E E A R N E R S
A N D C L E R IC A L W O R KE RS:
All items (1967-100) ......................................................................
Food and beverages .....................................................................
Food at hom e ...........................................................................
Cereals and bakery products.................................................
Meats, poultry, fish, and eggs................................................
Dairy products........................................................................
Fruits and vegetables.............................................................
Other foods at home..............................................................
Sugar and sweets................................................................
Fats and o ils ........................................................................
Nonalcoholic beverages......................................................
Other prepared foods..........................................................
Food away from home .............................................................
Alcoholic beverages....................................................................
Housing ..........................................................................................
Shelter .........................................................................................
Renters’ costs (12/84 = 100)...................................................
Rent, residential.....................................................................
Other renters’ costs ...............................................................
Homeowners' costs (12/84 = 100)...........................................
Owners’ equivalent rent (12/84 = 1 00)..................................
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 g a s ..............................................
Gas (piped) and electricity....................................................
Other utilities and public services...........................................
Housekeeping services............................................................
See footnotes at end of table.
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
Monthly Labor Review
September 1995
91
Current Labor Statistics:
Price Data
31. Continued— Consum er Price Indexes fo r Ail Urban Consum ers and fo r Urban W age Earners and Clerical W orkers: U.S. city
average, by expenditure category and com m odity or service group
(1982-84=100, unless otherwise indicated)
Annual
average
Series
1994
1995
1993
1994
July
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
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.Î
126.Î
130.^
128.9
126.5
145.4
151.2
132.2
129.4
125.8
129.2
129.3
126.9
148.7
154.9
129.8
126.7
124.6
124.2
130.8
125.8
148.3
155.1
130.2
127.2
125.3
124.5
129.9
125.3
151.5
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
130.7
126.5
130.6
127.7
127.9
153.5
157.2
132.1
129.1
127.8
128.1
123.9
127.4
146.9
157.1
129.6
126.4
125.6
123.2
122.4
125.5
151.5
156.5
127.4
124.0
123.1
120.0
123.5
124.2
149.3
156.8
Transportation .....................................................
Private transportation..............................................
New vehicles...............................................
New ca rs............................................
Used c a rs ............................................................
Motor fuel ...........................................................
Gasoline..........................................................
Maintenance and repair..............................................
Other private transportation........................................
Other private transportation commodities.............................
Other private transportation services....................................
Public transportation.......................................................
129.4
127.4
133.3
131.2
134.6
97.9
97.6
146.5
152.9
102.8
165.0
163.0
133.4
131.4
138.3
135.7
142.4
98.4
98.2
150.9
157.9
102.8
171.5
167.7
133.9
132.0
138.3
135.6
143.3
100.5
100.4
150.8
157.5
102.6
171.0
167.1
135.2
133.3
138.2
135.3
144.7
104.2
104.3
151.4
157.8
102.6
171.5
168.7
135.3
133.5
138.4
135.4
146.1
103.7
103.7
151.9
158.0
102.4
171.8
167.6
135.6
133.9
139.2
136.3
148.4
101.7
101.5
152.4
160.0
102.4
174.3
164.8
136.7
135.1
140.1
137.3
150.8
102.6
102.5
152.5
162.0
103.2
176.6
163.8
136.7
135.2
140.9
138.1
152.1
100.2
100.0
152.6
163.4
103.5
178.4
162.5
136.9
135.2
141.2
138.6
153.0
98.5
98.3
152.7
164.7
103.4
180.0
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
140.8
138.7
141.8
138.7
159.1
106.2
106.4
154.5
166.0
103.8
181.6
177.2
139.8
137.7
141.3
138.1
158.4
103.5
103.6
154.9
165.6
104.0
181.1
176.6
Medical c a re ................................................................
Medical care commodities .................................
Medical care services...........................................
Professional services ...............................................
Hospital and related services ...............................
200.9
193.2
202.7
185.2
229.2
210.4
198.6
213.0
193.4
242.7
210.8
199.0
213.4
193.9
243.2
211.5
199.5
214.2
194.4
244.4
212.0
199.3
214.9
194.9
245.2
213.4
199.9
216.4
196.0
246.9
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
219.2
201.5
223.2
201.9
253.4
220.2
202.2
224.3
202.7
255.0
Entertainment...........................................................
Entertainment commodities ................................
Entertainment services...............................................
144.1
132.9
160.5
148.2
135.5
166.7
148.4
136.0
166.5
148.3
135.9
166.5
148.6
136.0
167.0
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
151.2
137.4
171.2
151.5
137.7
171.4
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
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
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
203.0
226.5
146.8
143.5
150.9
228.4
213.6
229.8
203.3
226.3
146.9
143.3
151.3
229.2
213.8
230.6
All item s........................................................
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
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
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
149.9
136.7
147.8
129.9
130.3
126.4
135.2
128.1
149.9
136.2
148.0
128.9
128.9
124.0
134.2
127.9
Services............................................................
Rent of shelter (12/8 4=1 0 0 )...............................
Household services less rent of shelter (12/84=100).......
Transportation services................................
Medical care services........................................
Other services ..............................................
155.5
145.8
123.5
160.0
202.7
174.1
160.6
150.3
125.4
165.7
213.0
182.4
160.9
150.5
126.8
165.2
213.4
181.8
161.6
151.3
126.9
165.9
214.2
182.9
161.9
151.4
126.9
166.0
214.9
184.7
162.1
151.8
125.2
167.2
216.4
185.3
162.3
151.9
124.7
168.4
217.1
185.9
162.4
151.7
124.9
169.2
217.7
185.9
163.4
152.5
126.1
170.6
219.3
186.6
164.1
153.3
125.8
171.5
220.9
187.7
164.6
153.8
125.6
172.8
221.4
188.0
164.8
154.0
125.4
173.8
222.0
188.3
165.1
154.2
125.9
173.6
222.6
188.6
166.0
154.8
128.2
174.0
223.2
188.5
166.5
155.5
128.3
173.7
224.3
189.0
Special indexes:
All items less food ............................................
All items less shelter ......................................
All items less homeowners’ costs (12/84=100)............
All items less medical care...................................
Commodities less fo o d ...............................
Nondurables less food ...............................
Nondurables less food and apparel ..............
Nondurables...........................................
Services less rent of shelter (12/8 4=1 0 0 )...................
Services less medical c a re ..........................
Energy......................................................
All items less energy ............................
All items less food and energy ....................................
Commodities less food and energy.....................
Energy commodities .....................................
Services less energy.......................................
142.3
139.7
133.9
139.2
125.9
128.9
130.7
134.7
147.0
151.4
103.6
147.5
149.3
134.3
97.5
159.7
145.9
143.0
137.0
142.6
127.6
129.2
131.2
136.4
152.1
156.1
104.1
151.5
153.5
136.2
97.8
165.3
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
147.2
144.2
138.1
143.8
128.9
131.1
133.6
137.8
153.5
157.3
107.8
152.4
154.4
136.9
102.4
166.4
147.4
144.3
138.2
143.8
129.1
130.9
133.0
137.7
153.4
157.4
105.3
152.9
155.0
137.5
100.6
167.0
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
148.5
145.5
139.4
145.0
128.8
129.0
132.0
137.7
155.8
159.3
103.1
154.6
156.6
137.9
97.3
169.3
149.0
145.9
139.9
145.5
129.5
129.9
131.9
138.2
156.1
159.7
102.5
155.2
157.3
138.8
96.8
169.9
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
150.3
147.1
141.0
146.6
130.8
131.6
136.0
139 4
157.7
161.1
109.0
155.7
157.9
138.6
104.8
170.9
150.3
146.8
140.9
146.6
129.9
130 3
135.1
138 8
157 9
161.5
107.6
155.8
158 0
138.1
102.3
171.5
70.4
23.6
68.7
23.1
68.6
23.0
68.3
22.9
68.1
22.9
68.0
22.8
67.9
22.8
67.9
22.8
67.7
22.7
67.4
22.6
67.2
22.6
67.0
22.5
66.8
22.4
66.7
22.4
66.7
22.4
Purchasing power of the consumer dollar:
1982-84=$1.00....................................
1967 = $1.00......................................
92
Monthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
September 1995
32.
Consum er 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
Area1
Pricing
schedule2
Size A - More than
1 200 000 .............................
Size B - 360,000 to
1 200 000 .............................
Size C - 50,000 to
360 000 ................................
Size D - Nonmetropolitan (less
Size A - More than
1 200 000 .........................
Size B - 450,000 to
1 200 000 .............................
Size C - 50,000 to
450 000 ................................
Size D - Nonmetropolitan (less
Size A - More than
1 250 000 .............................
Size C - 50,000 to
330 000 ................................
Size classes:
A (1 2 /8 6 -1 0 0 )....................
B
....................................
c
.........................
D
......................................
Apr.
May
June
July
July
Mar.
Apr.
May
June
July
M
148.0
148.4
151.4
151.9
152.2
152.5
152.5
145.4
145.8
148.7
149.3
149.6
149.9
149.9
M
154.8
155.2
158.0
158.3
158.5
158.9
159.2
152.3
152.7
155.5
155.8
156.1
156.4
156.6
M
155.4
155.7
158.7
159.0
159.2
159.6
159.8
151.9
152.2
155.1
155.4
155.7
156.1
156.1
156.5
157.5
151.4
152.3
153.9
154.2
154.3
154.5
155.3
M
153.5
154.3
155.9
156.3
156.4
M
M
153.2
144.0
152.9
144.3
156.6
147.3
157.0
148.1
157.1
148.3
157.2
148.7
157.8
148.8
154.6
140.9
154.4
141.3
158.1
144.2
158.6
145.0
158.8
145.2
158.9
145.6
159.2
145.5
M
145.1
145.4
148.5
149.0
149.0
149.5
149.5
141.4
141.6
144.7
145.3
145.2
145.7
145.6
144.1
M
143.0
143.6
146.1
146.9
147.3
147.7
148.0
139.5
140.1
142.6
143.4
143.9
144.2
M
144.7
145.0
148.3
149.5
150.0
149.9
149.6
142.2
142.6
145.6
146.9
147.5
147.4
147.1
M
M
139.8
144.7
140.2
145.0
142.7
148.0
143.9
148.4
144.6
148.8
145.4
149.1
146.0
149.2
138.4
143.2
138.9
143.6
141.0
146.5
142.2
147.0
142.9
147.4
143.7
147.8
144.2
147.8
M
145.3
145.3
148.0
148.3
148.7
148.8
148.8
143.4
143.6
146.1
146.4
147.1
147.2
147.2
146.9
147.4
147.4
147.8
147.9
M
146.6
147.1
150.4
150.9
150.8
151.3
151.5
143.2
143.7
M
143.5
143.8
146.6
147.3
147.6
148.5
148.4
143.3
143.7
146.5
147.3
147.8
148.6
148.5
M
M
142.5
148.9
142.7
149.5
146.6
152.8
147.1
153.2
148.0
153.5
147.8
153.6
148.1
153.5
142.7
146.1
142.9
146.7
146.7
149.8
147.3
150.3
148.2
150.6
148.1
150.7
148.3
150.5
M
150.4
150.9
153.6
154.0
154.2
154.1
154.0
146.0
146.5
149.1
149.6
149.7
149.8
149.5
M
148.6
150.0
155.2
155.9
156.4
156.6
156.7
146.4
147.7
152.2
152.8
153.8
153.8
153.7
M
M
M
M
134.3
147.5
146.4
143.4
134.6
148.1
146.8
143.8
137.2
151.1
150.2
147.1
137.5
151.6
151.0
147.7
137.7
151.8
151.4
148.5
137.9
152.1
151.8
148.9
137.9
152.6
151.8
149.1
133.3
145.0
145.6
142.8
133.6
145.5
146.1
143.2
136.2
148.5
149.3
146.3
136.6
148.9
150.2
147.0
136.8
149.1
150.7
147.9
137.0
149.4
151.1
148.2
136.9
149.7
150.9
148.4
M
148.1
148.3
152.6
153.1
153.0
153.5
153.6
143.6
143.7
147.8
148.3
148.2
148.5
148.7
M
151.3
151.7
154.6
154.7
155.1
154.8
154.5
146.1
146.5
149.3
149.5
149.8
149.7
149.3
161.4
157.8
161.8
157.8
162.2
158.4
162.3
158.9
154.2
154.2
154.4
154.9
157.1
157.5
157.5
157.4
158.0
157.4
158.4
158.1
158.3
158.5
151.5
151.3
151.7
151.5
145.7
146.6
148.9
149.4
149.0
149.6
149.3
151.5
157.8
148.1
148.3
145.6
156.1
_
149.1
156.9
139.7
146.6
143.9
152.4
_
149.4
156.5
139.9
146.8
144.2
152.3
-
150.5
156.6
140.3
146.5
145.2
153.5
-
144.5
143.6
137.6
142.6
M
M
157.8
154.6
158.2
155.3
160.9
158.0
M
148.1
148.9
151.1
1
1
1
1
1
1
nallas-Ft Worth, T X ..............
Mar.
June
S e le c te d local areas
Chicago, IL-Northwestern IN ...
Los Angeles-Long
July
June
R e gio n an d a re a s ize3
Size A - More than
1 200 000 .............................
Size B - 500,000 to
1 200 000 .............................
Size C - 50,000 to
500 000 ................................
1995
1994
1995
1994
2
2
2
2
_
_
_
_
_
141.4
144.8
137.4
144.0
148.2
153.9
143.7
143.4
141.9
151.8
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
—
-
-
-
144.4
148.3
139.9
149.2
-
140.6
140.2
137.0
137.8
147.3
152.9
136.3
141.4
141.4
149.4
-
-
-
144.4
143.7
139.5
143.0
-
J __________
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.
Monthly Labor Review
September 1995
93
Current Labor Statistics:
33.
Price Data
Annual data: Consum er Price Index, U.S. city average, all item s and m ajor groups
(1982-84=100)
Series
94
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
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.......................................................
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
Consumer Price Index for Urban Wage Earners and
Clerical Workers:
All items:
Index................................................................
Percent change..............................................................
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
Monthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
September 1995
2.5
34.
Producer Price Indexes, by stage o f processing
(1982=100)
1995
1994
Annual average
G ro uping
1993
1994
Aug.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
July
Finished consumer goods ........................
Finished consumer foods.......................
Finished consumer goods excluding
foods ......................................................
Nondurable goods less food ...............
Durable g o o d s.....................................
Capital equipment.....................................
124.7
125.7
125.7
125.5
126.8
126.8
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
126.9
128.4
128.4
127.1
128.7
128.7
127.6
128.5
128.5
128.0
127.9
127.9
128.2
127.4
127.4
128.3
128.5
128.5
121.7
117.6
128.0
78.0
121.6
116.2
130.9
77.0
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
132.7
76.6
122.9
117.3
132.4
76.8
123.8
118.7
132.4
78.8
124.7
120.0
132.4
80.4
125.2
120.8
132.3
81.5
124.8
120.2
132.1
80.0
In te rm e d ia te m aterials, sup plies, and
c o m p o n e n ts ..........................................................
116.2
118.5
119.5
120.1
120.0
120.9
121.1
122.5
123.4
124.0
124.7
125.3
125.9
126.0
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
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
129.3
118.4
132.1
136.1
126.0
129.9
119.0
133.2
136.6
126.1
130.6
117.1
135.7
136.8
126.2
130.8
116.5
136.5
136.5
126.3
131.0
117.2
137.4
136.1
126.3
131.5
119.3
137.8
136.4
126.5
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
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
133.8
139.0
130.0
82.6
134.4
139.2
130.6
83.9
135.2
139.4
131.2
85.6
135.5
139.7
131.3
87.7
135.7
139.8
131.8
86.3
136.1
140.0
132.5
102.4
108.4
76.7
101.8
106.5
72.1
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
102.6
104.1
69.6
102.3
103.2
69.1
103.9
101.9
72.9
103.5
99.5
74.1
103.4
102.2
71.6
101.9
104.7
67.7
124.4
78.0
132.9
133.5
135.8
125.1
77.0
134.2
134.2
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
136.0
139.0
126.6
76.8
136.2
136.3
139.2
127.3
78.8
136.3
136.3
139.4
128.0
80.4
136.3
136.3
139.7
128.4
81.5
136.3
136.2
139.8
128.1
80.0
136.7
136.7
140.0
Finished g o o d s ....................................................
C ru d e m a te ria ls fo r fu rth e r p ro ce ssin g ...
Foodstuffs and feedstuffs .......................
Crude nonfood materials.........................
Sept.
S p ecia l groupings:
Finished goods, excluding fo o d s..............
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
fe e d s ........................................................
Intermediate foods and fe e d s...................
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
138.5
139.0
139.0
138.2
139.6
139.7
140.0
140.5
140.8
141.1
141.3
141.7
141.8
142.0
146.1
144.4
144.4
144.6
144.7
144.8
145.2
145.9
146.4
147.1
147.4
148.2
148.5
149.0
116.4
112.7
84.6
123.2
118.7
114.8
83.0
126.3
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
124.0
111.8
82.4
132.5
124.5
112.6
82.6
133.1
125.4
111.7
83.9
133.8
126.0
110.7
85.6
134.0
126.6
111.6
87.7
134.3
126.7
113.5
86.3
134.8
123.8
127.1
127.3
128.3
129.2
130.2
130.9
132.6
133.8
134.4
135.2
135.5
135.7
136.1
76.7
116.3
140.2
72.1
119.3
156.2
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
69.6
123.2
177.0
69.1
123.1
179.1
72.9
122.6
180.7
74.1
120.6
179.8
71.6
122.7
180.4
67.7
123.6
176.7
Monthly Labor Review
September 1995
95
Current Labor Statistics:
35.
Price Data
Producer price indexes fo r the net output o f m ajor industry groups
(December 1984=100, unless otherwise indicated)
Annual
1993
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
(1 2 /8 5 -1 0 0 )............................................
1994
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
72.1
101.9
88.4
68.7
71.2
102.3
91.3
66.9
70.7
103.7
93.7
65.7
73.5
105.0
94.4
69.4
May
June
July
76.4
69.7
93.3
76.2
73.3
81.4
93.2
71.1
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
14
118.8
120.5
120.4
120.5
120.7
120.8
120.9
122.4
123.3
123.6
20
21
22
119.1
118.7
218.0
113.6
120.7
120.1
187.8
113.6
121.5
120.1
187.7
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
123.1
120.8
188.7
115.5
123.4
121.1
190.6
115.7
23
119.2
119.7
119.7
119.7
119.8
119.7
119.8
120.0
120.3
120.6
120.6
24
25
26
148.3
125.4
120.2
154.4
129.7
123.7
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
155.0
132.0
139.1
155.5
132.1
141.4
155.0
132.5
143.7
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
149.6
130.3
82.5
117.0
130.6
120.4
117.5
150.3
132.0
79.5
117.9
131.3
120.7
118.7
150.8
133.6
76.2
118.8
131.7
121.1
119.7
151.7
134.4
77.8
119.5
132.1
121.4
121.7
152.4
136.1
73.5
120.1
132.5
121.6
122.9
154.7
138.4
74.3
121.3
133.3
122.4
126.6
155.6
140.6
74.6
121.8
133.7
123.1
128.2
156.4
141.4
75.3
122.5
133.8
123.8
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
120.6
120.8
121.2
121.6
121.8
122.6
123.6
124.1
124.6
124.7
124.9
125.1
35
116.8
117.5
117.6
117.7
117.7
117.7
117.8
118.3
118.6
118.7
119.0
119.0
119.3
119.3
36
37
112.0
126.3
112.7
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
113.3
132.2
113.1
132.0
113.1
132.0
113.4
131.8
113.2
131.9
113.2
131.7
38
120.8
122.1
122.2
122.0
122.3
122.6
122.6
122.9
123.4
123.4
123.7
123.6
124.1
124.6
39
121.5
123.3
123.5
123.6
123.6
123.8
124.0
125.0
125.3
125.4
125.5
125.6
125.8
126.1
42
43
44
45
46
119.8
99.7
105.6
96.6
101.9
119.8
100.0
108.5
102.6
102.2
119.8
100.1
109.0
102.9
102.3
119.8
100.3
108.5
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
104.2
132.1
102.8
109.6
110.9
104.4
132.1
102.6
110.1
110.9
104.6
132.1
101.9
110.1
110.9
104.5
132.1
102.2
113.6
110.9
104.4
132.1
102.6
114.2
110.7
104.7
132.3
103.5
115.6
110.7
T o ta l m a n u fa c tu rin g in d u s tr ie s ......................
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..........................
1995
10
12
13
T o ta l m ining In d u s tr ie s ......................................
Metal mining................................................
Coal mining (12/85=100)..........................
Oil and gas extraction (1 2/8 5=1 0 0 ).........
Mining and quarrying of nonmetallic
minerals, except fu e ls ..............................
1994
*
SIC
In d u stry
72.0
94.2
92.0
68.6
74.3
99.1
92.1
71.2
72.6
99.4
91.0
69.1
70.0
103.4
91.0
65.2
123.1
123.1
123.3
123.7
124.0
120.2
190.8
116.0
124.5
120.2
195.3
116.6
124.5
120.4
195.3
116.5
124.4
121.4
195.1
116.7
120.5
120.4
120.5
154.6
132.9
145.6
153.1
133.4
148.2
154.1
133.4
149.6
157.9
144.2
83.1
124.1
134.2
124.5
128.9
159.4
144.7
78.6
124.2
134.2
124.5
128.7
S e rv ic e industries:
Motor freight transportation
and warehousing (06/93=100) ............
U.S. Postal Service (06/8 9=1 0 0 )..............
Water transportation (12/9 2=1 0 0 )............
Transportation by air (12/92=100) ...........
Pipelines, except natural gas (12/86=100)
- Data not available.
96
Monthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
September 1995
36.
Annual data: Producer Price Indexes, by stage o f 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:
T o ta l....................................................................
Foods ...............................................................
Energy..............................................................
O the r................................................................
In te rm e d ia te m aterials, supplies, and
com p o n en ts:
T o ta l....................................................................
Foods ...............................................................
Energy..............................................................
O the r................................................................
C ru d e m a terials fo r fu rth e r processing:
T o ta l....................................................................
Foods ...............................................................
Energy..............................................................
O the r................................................................
37.
U.S. expo rt price indexes by Standard International T rade Classification
(1990=100, unless otherwise indicated)
C a te g o ry
Fo o d an d live a n im a ls .................................................................................................
Meat and meat preparations.....................................................................
Cereals and cereal preparations...............................................................
Vegetables, fruit, and nuts, prepared fresh or d ry ....................................
C ru d e m a terials, inedible , e x c e p t f u e l s ..............................................................
Hides, skins, and furskins, ra w ..................................................................
Oilseeds and oleaginous fru its ..................................................................
Crude rubber (including synthetic and reclaimed) ....................................
Cork and w o o d ..........................................................................................
Pulp and waste paper................................................................................
Textile fibers and their waste ...................................................................
Crude fertilizers and crude minerals.........................................................
Metalliferous ores and metal s cra p ..........................................................
SITC
Rev. 3
1995
1994
Aug.
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
0
01
04
05
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
108.2
112.4
103.1
116.8
111.3
113.5
106.8
122.5
112.4
113.0
110.2
122.2
113.7
115.0
113.9
117.2
2
21
22
23
24
25
26
27
28
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
115.4
157.9
145.9
122.7
97.2
124.4
127.4
109.6
93.7
115.9
157.3
156.0
132.5
98.4
124.9
131.0
108.6
96.3
120.7
159.5
168.3
130.7
98.2
130.2
131.1
107.3
95.0
119.0
158.2
167.0
131.4
99.3
134.1
131.9
103.5
96.7
117.7
157.0
172.8
133.9
98.2
133.5
Coal, coke, and briquettes........................................................................
Petroleum, petroleum products, and related
materials................................................................................................
3
32
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
90.8
96.4
92.6
96.5
93.2
97.7
33
87.0
81.1
80.6
81.1
82.8
82.8
82.4
81.9
83.9
86.9
87.2
A n im al an d v e g e ta b le oils, fa ts , an d w a x e s .....................................................
4
109.0
116.2
118.1
119.1
132.1
134.7
124.2
122.0
116.1
113.9
114.8
C h em ica ls an d re la te d pro d u cts , n.e.s.................................................................
5
54
55
57
58
59
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
114.7
115.4
108.3
110.4
141.9
106.5
113.3
116.7
108.3
110.7
144.6
108.4
114.7
117.4
108.4
110.5
143.9
109.4
114.9
116.7
109.5
110.2
141.4
109.6
115.1
6
62
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
113.9
115.8
115.1
114.7
116.3
116.0
115.8
116.3
64
66
68
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
123.8
109.3
115.4
128.1
109.1
115.8
127.4
109.2
113.5
7
71
72
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
104.1
115.3
111.1
104.2
114.5
111.6
104.5
114.9
112.1
104.5
115.0
112.2
104.7
114.9
112.6
74
75
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
77.1
112.0
76.7
111.2
76.5
76
77
78
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
102.2
107.8
106.0
102.9
107.8
106.2
102.9
107.9
106.7
104.0
108.0
87
111.9
112.5
112.2
113.1
112.6
113.5
113.4
113.2
113.4
113.2
113.9
M ine ra l fuels, lubrica nts , and re la te d p r o d u c ts ..............................................
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.................................... ................
M an u fa c tu re d g o o d s c lassified c h ie fly by
m a te r ia ls ..........................................................................................................................
Rubber manufactures, n.e.s........................................................................
Paper, paperboard, and articles of paper, pulp,
and paperboard........................................................................................
Nonmetallic mineral manufactures, n.e.s...................................................
Nonferrous m etals.....................................................................................
M a ch in ery and tra n s p o rt e q u ip m e n t.......................................................... .........
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............................................................................................
P ro fe s s io n a l, s cien tific, and co n tro llin g
in s tru m e n ts an d a p p a r a tu s ................................................................................
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
Monthly Labor Review
September 1995
97
Current Labor Statistics: Price Data
38.
U.S. im port price indexes by Standard International T rade Classification
(1990=100, unless otherwise indicated)
C a te g o ry
1994
1995
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
0
01
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
115.9
86.6
117.8
85.1
116.4
85.2
03
04
05
06
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
102.2
114.4
98.1
127.2
91.6
104.1
99.6
126.3
96.3
111.6
98.4
126.1
101.4
110.6
103.9
07
202.2
212.0
194.5
172.3
172.2
168.6
183.7
176.6
178.3
167.4
1
11
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
114.9
114.8
2
23
24
25
27
28
29
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
90.2
106.6
140.1
123.1
168.6
141.1
108.1
92.4
105.8
155.5
122.2
166.3
139.2
109.5
97.8
105.6
146.5
123.1
156.8
131.0
116.0
100.4
106.3
160.8
M ineral fuels, lubricants, an d re la te d p r o d u c ts ..............................................
3
73.5
73.9
76.9
75.3
76.0
77.8
79.1
82.5
85.4
82.7
Petroleum, petroleum products, and related
materials................................................................................................
Gas, natural and manufactured..............................................................
Electrical energy.....................................................................................
33
34
35
72.6
Ô7.4
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
79.5
78.0
82.6
77.9
77.4
85.6
79.1
81.1
82.7
79.9
78.8
A nim al and v e g e ta b le oils, fats , and w a x e s .....................................................
4
140.0
141.6
144.1
155.0
152.2
145.4
152.4
154.4
157.6
159.0
C h e m ic a ls and re la te d produ cts , n .e .s .................................................................
5
52
53
54
55
56
57
58
59
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
121.6
116.8
112.0
106.8
115.5
103.8
111.3
112.0
110.9
124.7
120.1
113.1
109.0
116.5
105.0
112.5
113.2
109.0
129.1
124.1
112.8
110.3
117.4
105.6
112.3
114.3
108.6
128.0
123.4
111.0
109.8
117.9
106.8
6
62
103.0
101.5
103.9
102.5
105.4
102.6
106.4
102.3
107.4
102.4
108.8
102.1
109.1
102.8
110.8
103.7
112.1
105.1
111.7
105.0
64
66
68
69
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
114.4
110.8
105.9
108.4
119.5
111.3
106.4
110.0
125.2
111.2
106.5
110.8
125.1
111.4
103.8
110.8
7
72
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
110.1
117.1
110.1
117.2
74
75
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
84.2
116.7
84.0
76
77
78
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
97.6
106.9
115.8
98.4
107.6
116.3
98.9
109.0
116.8
98.7
108.8
116.9
85
101.0
101.0
101.3
101.1
100.7
101.0
101.1
101.4
101.5
101.9
88
110.8
111.1
110.8
110.6
109.9
110.7
111.0
113.4
115.5
115.5
Fo o d a nd live a n im a ls ..................................................................................................
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 ..................................................................................................
B e v e ra g e s and to b a c c o .............................................................................................
Beverages................................................................................................
C ru d e m aterials, inedible, e x c e p t f u e l s ..............................................................
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..........................................
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...................................................
M an u fa c tu re d g o o d s c lassified c h ie fly by m aterial .....................................
Rubber manufactures, n.e.s.....................................................................
Paper, paperboard, and articles of paper pulp,
paper, or paperboard ...........................................................................
Nonmetallic mineral manufactures, n.e.s.................................................
Nonferrous m etals...................................................................................
Manufactures of metals, n.e.s..................................................................
M a c h in e ry and tra n s p o rt e q u ip m en t .................................................................
Machinery specialized for particular industries......................................
General industrial machinery and equipment, n.e.s.,
and machine p arts................................................................................
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........................................................................
98
SITC
Rev.3
Monthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
September 1995
39.
U.S. export price indexes by end-use category
(1990 = 100 unless otherwise indicated)
1994
1995
C a te g o ry
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
A L L C O M M O D IT IE S ........................................................................................
103.8
104.4
105.1
105.8
106.7
107.3
107.9
108.9
109.2
109.4
Foods, feeds, and beverages .......................................................
Agricultural foods, feeds, and beverages ...................................
Nonagricultural (fish, beverages) food
products....................................................................................
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
107.8
111.1
109.5
107.9
112.1
112.8
113.0
113.5
117.1
122.1
123.1
122.6
122.5
Industrial supplies and materials....................................................
104.3
106.0
107.9
109.9
112.5
114.1
115.3
117.1
117.9
117.7
Agricultural industrial supplies
and materials ............................................................................
107.1
107.7
109.7
114.4
117.7
118.7
121.8
120.7
120.3
120.7
Fuels and lubricants ...................................................................
Nonagricultural supplies and materials,
excluding fuel and building materials.......................................
Selected building materials.........................................................
90.3
90.0
90.6
91.4
91.5
91.6
91.0
92.9
94.2
94.8
102.6
147.2
104.9
147.3
107.1
148.6
109.2
149.7
112.2
151.4
114.2
153.3
115.6
153.4
117.9
153.5
119.0
151.1
118.6
150.7
Capital goods..................................................................................
Electric and electrical generating
equipment.................................................................................
Nonelectrical machinery..............................................................
103.7
103.6
103.7
103.6
103.9
104.0
104.3
104.7
104.7
104.9
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
101.5
107.8
101.5
108.1
101.8
Automotive vehicles, parts, and engines......................................
106.7
107.2
107.2
107.3
107.4
107.7
107.4
107.4
107.4
107.6
Consumer goods, excluding automotive.......................................
Nondurables, manufactured........................................................
Durables, manufactured ..............................................................
Nonmanufactured consumer goods............................................
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
-
109.1
111.3
106.9
99.9
109.3
111.8
106.8
.0
109.5
111.9
107.3
.0
109.5
111.9
107.2
99.4
Agricultural commodities................................................................
Nonagricultural commodities .........................................................
101.7
104.2
101.6
104.9
103.2
105.5
105.7
106.0
105.6
107.0
106.1
107.7
107.6
108.1
109.7
109.0
110.3
109.2
111.8
109.3
- Data not available.
40.
U.S. im port price indexes by end-use category
(1990 = 100)
1994
1995
C a te g o ry
Sept.
Oct.
Nov.
Dec.
Jan.
Feb.
Mar.
Apr.
May
June
A L L C O M M O D IT IE S ........................................................................................
102.8
103.5
104.2
104.1
104.4
105.1
105.7
106.7
107.7
107.3
Foods, feeds, and beverages .......................................................
Agricultural foods, feeds, and beverages ...................................
Nonagricultural (fish, beverages) food
products....................................................................................
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
117.9
119.2
116.6
123.5
125.3
125.7
126.7
125.1
125.0
126.7
126.5
125.7
125.5
Industrial supplies and materials...................................................
90.6
91.5
93.8
93.7
94.8
96.6
97.7
99.9
101.7
100.2
Fuels and lubricants ......................................................................
Petroleum and petroleum products ............................................
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
83.7
82.1
86.6
85.0
83.9
82.1
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 ...................................
93.0
94.7
96.8
100.1
104.7
107.2
112.3
117.1
121.3
123.3
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
106.1
103.0
113.7
122.4
107.1
104.1
114.2
121.9
106.9
106.4
114.3
117.9
105.2
107.0
Capital goods.................................................................................
Electric and electrical generating equipment .............................
Nonelectrical machinery..............................................................
Transportation equipment, excluding motor
vehicles and spacecraft (12/92 — 100) ..................................
Automotive vehicles, parts and engines.......................................
104.8
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
105.1
109.2
103.7
105.2
109.6
103.8
106.2
111.0
104.8
107.1
112.3
105.7
107.1
112.2
105.7
105.2
111.6
105.7
112.9
105.8
113.2
105.3
113.0
-
-
-
-
-
-
112.9
113.2
113.6
114.3
114.9
115.0
Consumer goods, excluding automotives......................................
Nondurables, manufactured........................................................
Durables, manufactured ..............................................................
Nonmanufactured consumer goods............................................
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
106.9
107.0
106.2
112.1
107.2
107.0
106.6
114.2
107.7
107.6
107.2
112.8
107.9
107.9
107.3
112.5
- Data not available.
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
Monthly Labor Review
September 1995
99
Current Labor Statistics:
41.
Price and Productivity Data
U.S. international price indexes fo r selected categories of services
(1990=100 unless otherwise indicated))
1993
1994
1995
C a te g o ry
June
Sept.
Dec.
Mar.
June
Sept.
Mar.
Dec.
June
Air freight (inbound) ..............................................................
Air freight (outbound)............................................................
106.4
96.6
106.6
95.6
106.1
96.4
105.9
96.5
108.1
96.2
108.6
96.2
110.4
97.3
115.3
98.4
118.0
98.2
Air passenger fares (U.S. carriers) ......................................
Air passenger fares (foreign carriers)...................................
Ocean liner freight (inbound)................................................
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
121.4
118.1
106.2
113.8
110.0
106.6
116.1
113.8
108.5
128.6
125.2
106.6
42.
Indexes o f productivity, hourly com pensation, and unit costs, quarterly data seasonally adjusted
(1982 = 100)
Quarterly Indexes
Item
1992
IV
1993
I
II
1994
III
IV
I
II
1995
III
IV
I
II
Business:
Output per hour of all persons.............................
Compensation per hour........................................
Real compensation per h o u r................................
Unit labor costs .....................................................
Unit nonlabor payments .......................................
Implicit price deflator ............................................
116.8
157.7
107.1
135.1
150.2
140.1
116.2
158.7
107.0
136.6
149.5
140.8
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
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
121.3
167.9
107.3
138.4
159.3
145.3
122.2
169.5
107.4
138.7
159.8
145.6
115.0
156.4
106.2
136.1
152.1
141.2
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
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
119.3
166.1
106.2
139.2
162.1
146.6
120.2
167.6
106.2
139.4
162.6
146.9
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
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
125.8
160.5
102.6
124.2
127.5
116.0
224.0
136.3
130.4
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
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
140.5
157.7
100.8
112.3
N o n fa rm business:
Output per hour of all persons.............................
Compensation per hour........................................
Real compensation per h o u r................................
Unit labor costs ....................................................
Unit nonlabor payments .......................................
Implicit price deflator ............................................
N o n fin an cial co rp o ra tio n s:
Output per hour of all employees........................
Compensation per hour........................................
Real compensation per h o u r................................
Total unit co sts.....................................................
Unit labor costs ..................................................
Unit nonlabor co sts............................................
Unit profits.............................................................
Unit nonlabor payments .......................................
Implicit price deflator ............................................
-
-
M anufacturin g:
Output per hour of all persons.............................
Compensation per h our........................................
Real compensation per h o u r................................
Unit labor costs ....................................................
- Data not available.
100
Monthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
September 1995
141.2
157.9
100.1
111.8
43.
Annual indexes o f m ultifactor productivity and related m easures, selected years
(1987=100)
Item
1960
1973
1970
1980
1987
1986
1988
1989
1990
1992
1991
1993
P riv a te business:
Productivity:
Output per hour of all persons..........................
Output per unit of capital services.....................
Multifactor productivity.......................................
O utput...................................................................
Inputs:
Labor in p u t.........................................................
Capital services ..................................................
Combined units of labor and capital inp u t........
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
53.6
46.1
74.2
49.8
65.8
65.0
78.7
56.6
71.3
69.1
86.8
75.5
83.2
84.2
96.8
97.0
96.8
99.9
100.0
100.0
100.0
100.0
104.2
102.9
103.8
99.6
107.2
105.6
106.7
99.7
107.8
108.2
107.9
102.1
106.5
110.0
107.5
106.3
107.5
111.6
108.8
108.1
110.1
113.8
111.3
107.9
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
49.9
47.0
72.0
47.7
63.9
64.1
76.9
54.5
69.6
68.3
85.7
74.2
82.1
83.8
96.6
96.7
96.7
99.9
100.0
100.0
100.0
100.0
104.4
103.2
104.0
99.6
107.6
106.1
107.1
99.9
108.3
108.8
108.5
102.3
106.8
110.8
108.0
106.7
108.0
112.6
109.3
108.7
110.9
115.0
112.1
108.2
P rivate n o n fa rm business:
Productivity:
Output per hour of all persons..........................
Output per unit of capital services.....................
Multifactor productivity.......................................
O utput...................................................................
Inputs:
Labor input .........................................................
Capital services ..................................................
Combined units of labor and capital in p u t........
Capital per hour of all persons.............................
NOTE: Productivity and output in this table have not been revised for
consistency with the December 1991 comprehensive revisions to the
44.
National Income and Product Accounts,
Annual indexes o f productivity, hourly com pensation, unit costs, and prices, selected years
(1982 = 100)
Item
1960
1970
1973
1983
1985
1987
1988
1989
1990
1991
1992
1993
1994
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
119.4
164.5
107.1
137.8
156.4
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
117.4
162.6
105.9
138.5
159.2
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
124.4
157.7
102.7
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:
Output per hour of all persons.............................
Compensation per h our........................................
Real compensation per h o u r................................
Unit labor c o s ts ....................................................
Unit nonlabor payments .......................................
Implicit price deflator ............................................
N o n fa rm business:
Output per hour of all persons.............................
Compensation per h our........................................
Real compensation per h o u r................................
Unit labor c o s ts ....................................................
Unit nonlabor payments .......................................
Implicit price deflator ............................................
N o n fin an cial co rp o ra tio n s:
Output per hour of all employees........................
Compensation per hour........................................
Real compensation per h o u r................................
Total unit co sts.....................................................
Unit labor costs ..................................................
Unit nonlabor co sts............................................
Unit profits.............................................................
Unit nonlabor payments .......................................
Implicit price deflator ............................................
M anufacturin g:
Output per hour of all persons.............................
Compensation per hour........................................
Real compensation per h o u r................................
Unit labor c o s ts ....................................................
Unit nonlabor payments .......................................
Implicit price deflator ............................................
-
-
-
-
-
-
-
-
-
“
- Data not available.
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
Monthly Labor Review
September 1995
101
Current Labor Statistics:
45.
Productivity Data
Annual indexes o f output per hour fo r selected industries
(1987 = 100)
Industry
SIC
1979
1985
1986
1987
1988
1989
1990
1991
Iron mining, usable ore .....................................
Copper mining, recoverable metal....................
Coal mining.......................................................
Crude petroleum and natural g a s .....................
Nonmetallic minerals, except fuels...................
101
102
12
131
14
51.7
42.4
68.9
173.5
86.5
51.8
48.5
54.5
110.3
92.6
76.6
93.6
85.1
83.0
95.1
79.6
109.7
92.4
90.3
95.1
100.0
100.0
100.0
100.0
100.0
103.7
109.8
110.6
101.0
102.2
99.5
107.8
116.5
98.1
101.9
90.0
104.5
118.5
97.0
108.3
87.0
102.9
122.1
98.1
103.6
Meatpacking plants...........................................
Sausages and other prepared meats...............
Poultry dressing and processing.......................
Cheese, natural and processed.......................
Fluid m ilk...........................................................
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
65.1
67.2
58.0
56.6
49.5
66.0
80.1
68.5
65.6
59.3
24.1
75.0
92.8
81.7
79.8
62.7
74.0
86.6
80.5
74.2
69.3
47.1
98.3
97.8
100.5
94.7
88.3
93.0
97.0
95.8
97.1
68.6
74.6
98.7
98.6
95.6
101.1
94.0
98.4
104.9
95.9
98.6
72.7
97.3
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
99.5
105.6
95.9
106.4
103.9
100.2
95.1
102.0
98.6
83.8
96.6
92.2
99.8
101.2
104.3
106.7
92.5
98.9
101.6
96.0
98.6
103.0
92.9
93.6
107.7
101.1
108.0
96.2
92.3
107.0
102.0
106.9
104.7 ■
94.9
90.8
114.2
98.9
110.7
103.4
98.7
107.4
105.3
101.1
100.1
Prepared feeds for animals and fo w ls.............
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
51.6
82.3
76.7
75.9
43.3
49.2
93.2
79.4
66.5
83.8
96.4
78.3
63.8
64.4
93.8
90.3
96.9
95.6
96.6
73.4
73.7
85.2
88.0
93.5
95.2
100.1
96.9
80.8
85.1
91.4
91.2
95.3
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
101.2
93.8
97.5
95.3
99.1
109.9
99.2
106.8
103.1
93.2
97.4
87.9
102.0
119.3
92.9
107.3
106.6
96.2
100.9
91.1
110.9
126.7
87.1
112.9
107.2
92.9
101.3
93.4
110.1
135.1
84.8
119.2
Cotton and synthetic broadwoven fabrics.......
Hosiery ..............................................................
Yarn spinning m ills............................................
Men’s and boys’ suits and coats......................
221,2
2251,52
2281
231
58.1
63.2
55.9
75.6 •
75.6
93.3
68.3
95.9
93.4
100.9
89.6
106.3
99.0
102.5
93.2
103.5
100.0
100.0
100.0
100.0
100.3
107.0
98.6
102.5
104.5
109.3
108.4 ' 106.0
103.6
106.7
101.9
98.8
115.2
111.3
106.3
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 w o o d ...........................
Pulp, paper, and paperboard m ills....................
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
68.3
84.0
104.2
80.5
80.2
67.7
91.2
71.9
75.6
71.6
82.5
70.6
67.1
70.3
86.4
90.7
73.3
83.0
95.4
89.1
79.6
65.6
72.9
90.4
82.8
72.5
86.2
117.0
76.7
77.3
87.2
90.7
94.1
93.5
95.1
97.4
87.1
84.5
88.3
99.6
93.3
98.6
98.8
77.2
99.4
96.9
87.6
99.6
90.0
99.7
102.3
98.8
102.2
85.2
83.2
90.4
98.7
100.2
100.6
101.7
83.1
96.2
100.6
93.3
102.8
88.5
101.8
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
101.7
97.4
98.3
97.8
98.3
100.3
103.4
101.0
99.8
100.6
99.2
94.8
96.0
102.9
99.6
99.6
97.4
101.0
96.5
97.7
91.0
97.4
102.0
108.9
100.1
101.0
100.0
105.0
94.2
99.0
103.2
97.7
101.1
93.6
101.5
95.4
97.9
93.7
90.2
107.3
112.0
98.8
98.5
103.9
105.7
95.8
95.7
102.1
100.3
99.4
91.4
105.0
98.2
95.8
92.6
90.7
113.0
114.2
100.2
103.4
107.3
110.3
99.1
93.0
101.5
100.0
102.8
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 o n ly ......................................
Agricultural chemicals, not
elsewhere classified.......................................
2812
2816
38.4
72.6
50.8
67.8
70.8
84.4
97.7
88.6
100.0
100.0
100.9
101.2
92.6
107.3
90.7
102.5
84.0
96.3
2819 pt.
2823,24
2841
2844
285
90.6
38.4
89.1
88.6
63.2
91.5
70.9
91.0
93.6
79.8
87.3
79.3
91.5
90.3
96.9
88.6
90.8
92.3
96.6
98.0
100.0
100.0
100.0
100.0
100.0
96.8
102.7
103.4
105.0
103.0
104.3
103.5
110.7
101.6
106.6
106.8
98.3
132.1
100.8
111.4
99.0
97.1
131.7
103.4
111.2
2869
2873
2874
2875
73.1
65.4
62.4
90.5
93.0
72.7
68.3
110.9
87.8
100.7
84.2
100.8
92.3
90.5
79.6
95.1
100.0
100.0
100.0
100.0
110.7
101.7
93.4
103.4
109.9
105.4
85.6
110.8
99.5
108.9
104.5
108.7
93.2
110.1
114.5
109.3
2879
-
74.3
83.6
92.9
93.2
100.0
108.4
108.9
106.2
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
84.0
56.0
79.3
82.6
63.9
80.6
84.7
89.3
100.5
94.9
92.6
102.2
100.0
100.0
100.0
105.3
104.6
107.3
109.6
107.2
96.3
109.1
108.3
100.9
106.7
109.5
93.0
308
314
3221
324
3251,53,59
3255
3271,72
3273
72.8
89.9
75.2
71.3
78.5
80.1
92.5
99.1
74.3
94.5
83.8
68.7
79.0
93.9
91.3
96.2
88.2
99.9
93.4
91.8
94.2
94.9
99.5
93.7
88.9
101.7
98.5
97.1
95.5
100.8
104.4
96.1
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
98.4
102.4
101.1
103.3
103.9
101.3
102.3
100.3
97.5
101.4
104.8
110.1
96.7
97.3
105.2
101.0
100.4
93.0
112.5
112.5
100.5
102.2
104.6
99.7
100.9
93.3
114.9
108.3
95.1
96.2
105.9
96.1
Steel ..................................................................
Gray and ductile iron foundries........................
Steel foundries ..................................................
Primary copper..................................................
Primary aluminum............................ .s...............
Copper rolling and drawing ..............................
Aluminum rolling and drawing..........................
331
3321
3324,25
3331
3334
3351
3353,54,55
64.2
91.3
105.8
32.8
73.6
77.5
79.0
65.9
92.4
104.5
41.1
74.7
82.0
84.3
85.8
96.9
99.5
73.8
97.6
86.2
85.7
89.7
99.3
104.9
88.7
102.7
92.3
95.8
100.0
100.0
100.0
100.0
100.0
100.0
100.0
113.4
106.8
95.3
103.7
102.2
100.0
96.9
108.5
104.1
96.6
96.8
104.6
94.1
91.2
110.5
104.1
95.9
86.3
106.3
93.9
92.4
108.1
99.3
93.2
84.7
110.3
96.9
92.0
See footnotes at end of table.
102
1973
Monthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
September 1995
45. Continued— Annual indexes o f output per hour fo r selected industries
(1987 = 100)
Industry
Metal cans ........................................................
Hand and edge tools, not elsewhere
classified.........................................................
Heating equipment, except electric ..................
Fabricated structural m etal...............................
Metal doors, sash, and trim ..............................
Bolts, nuts, rivets, and washers.......................
Automotive stampings......................................
Metal stampings, not elsewhere
classified.........................................................
SIC
1973
1979
1985
1986
1987
1988
1989
1990
1991
3411
59.2
75.2
99.2
95.9
100.0
107.4
109.0
119.1
126.0
3423
3433
3441
3442
3452
3465
108.6
78.0
98.1
90.5
75.8
74.9
111.6
86.2
86.0
92.6
78.9
81.4
98.8
91.9
98.6
104.8
88.8
94.5
97.1
96.2
98.8
102.0
91.0
95.7
100.0
100.0
100.0
100.0
100.0
100.0
100.9
112.7
98.9
102.4
97.0
104.5
102.1
103.2
94.7
101.5
93.8
104.7
96.4
111.2
96.8
97.0
93.7
100.8
95.0
115.4
98.3
94.7
96.2
104.2
3469
96.8
100.2
88.6
93.9
100.0
99.6
98.3
95.1
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
93.6
140.8
95.7
116.0
94.4
120.0
93.9
121.4
100.0
100.0
101.3
99.2
101.0
101.7
101.9
106.5
101.2
113.3
3519
3523
3524
3531
3532
3533
83.1
108.6
70.0
87.9
102.2
105.9
86.4
112.6
83.3
91.5
89.3
100.6
92.0
101.6
82.4
92.2
93.7
92.3
98.5
95.7
93.2
99.1
95.1
95.0
100.0
100.0
100.0
100.0
100.0
100.0
105.1
112.5
97.2
107.2
102.2
99.3
110.9
123.1
91.9
109.7
107.3
104.6
105.0
130.6
93.4
108.9
99.0
107.4
98.9
123.6
94.5
98.2
90.7
109.2
Metal-cutting machine tools .............................
Metal-forming machine to o ls ............................
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
112.5
105.9
84.0
108.0
87.6
100.3
102.9
100.9
98.5
100.6
91.4
110.2
86.1
98.8
82.0
89.9
93.1
92.3
91.9
91.6
92.2
98.1
98.9
92.0
93.7
95.0
92.7
94.1
96.0
95.8
95.7
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
96.1
113.8
99.3
105.8
102.4
104.1
103.5
108.8
101.2
109.9
104.6
101.5
98.2
106.1
105.7
117.1
103.1
100.6
107.4
103.5
92.1
109.2
104.6
110.9
100.2
91.9
109.2
102.7
88.3
111.8
102.6
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 lam ps....................................................
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
100.2
88.2
89.0
61.8
70.1
72.3
109.8
87.5
89.7
79.1
86.8
84.7
97.0
95.1
94.9
90.3
104.1
93.8
99.3
95.9
96.8
104.6
101.2
97.4
100.0
100.0
100.0
100.0
100.0
100.0
102.9
109.5
103.3
116.4
103.1
106.6
103.9
106.6
103.8
99.4
106.9
100.8
107.8
107.8
102.4
100.1
107.4
104.8
111.4
105.7
106.4
106.2
112.3
111.4
3639
3641
3645,46,47,48
3651
371
3721
3825
386
63.7
61.3
84.1
22.3
68.7
79.2
63.7
58.9
76.1
76.1
86.2
39.1
77.7
98.6
70.8
79.0
86.3
94.2
96.7
96.3
95.3
94.2
95.4
86.1
89.1
91.5
103.0
106.9
95.1
93.5
90.4
94.1
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
101.0
101.1
98.3
107.3
103.2
104.8
106.6
106.8
98.4
86.2
97.2
122.3
103.3
108.2
109.6
115.7
91.9
91.4
96.5
128.4
102.5
109.8
108.2
111.7
81.1
97.0
94.7
142.0
96.9
126.7
111.5
115.6
Railroad transportation, revenue traffic............
Bus carriers, class 1 .........................................
Trucking, except local ......................................
Air transportation ..............................................
Petroleum pipelines ..........................................
Telephone communications..............................
Electric utilities ..................................................
Gas utilities.......................................................
Scrap and waste materials...............................
4011
411,13,14 pts.
4213
4512,13,22 pts.
4612,13
481
491,493 pt.
492,493 pt.
5093
49.3
116.8
69.5
54.3
93.2
46.2
88.4
145.5
-
54.0
108.3
83.9
75.5
96.9
68.7
95.3
141.4
81.1
79.8
96.1
93.8
92.0
99.9
92.6
93.0
111.9
93.4
86.1
95.6
96.8
93.8
102.0
98.1
95.2
102.1
97.7
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
109.3
107.9
105.2
99.5
104.8
107.8
104.9
105.5
94.3
115.4
104.6
109.4
95.1
103.2
113.4
107.7
103.6
87.8
122.6
128.1
92.2
102.5
115.1
110.0
95.0
92.2
92.5
99.1
121.8
113.3
94.2
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
83.3
60.8
148.9
109.1
125.6
85.1
71.1
59.5
77.6
58.9
76.2
81.3
83.9
59.8
97.5
74.0
123.3
106.8
112.3
86.3
80.1
73.7
82.3
72.8
75.4
90.9
91.0
72.9
95.6
92.6
129.2
105.7
87.6
99.8
94.5
93.5
98.3
99.8
103.1
97.6
94.8
94.9
101.6
97.4
106.7
103.8
93.6
101.6
94.3
101.8
100.7
107.0
103.3
105.5
101.2
106.5
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
108.7
99.4
97.3
98.6
94.2
102.7
106.5
102.4
102.6
99.4
101.3
102.7
99.5
101.1
115.4
97.4
113.7
95.8
87.3
103.8
108.9
104.0
102.3
102.9
103.2
107.3
102.6
108.7
110.5
94.8
132.1
94.8
84.8
107.1
114.2
101.0
101.6
106.7
101.5
106.3
104.3
111.2
102.5
99.2
130.2
94.0
90.0
105.6
114.6
102.0
102.0
110.1
102.3
105.5
104.2
117.4
573
45.6
53.0
89.3
94.1
100.0
122.2
122.0
131.4
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
110.3
92.2
95.0
81.2
102.4
110.8
85.9
109.3
106.6
101.8
90.2
84.1
109.7
109.9
89.4
105.0
96.2
102.5
101.9
94.3
101.2
103.3
96.1
99.4
99.3
101.6
93.8
96.2
98.9
100.8
96.9
96.1
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
102.6
102.0
99.9
103.4
95.8
97.1
93.3
105.6
101.9
102.8
104.7
102.2
91.4
98.6
96.0
107.8
103.1
104.1
110.6
108.6
90.6
99.0
91.3
106.3
104.5
105.5
112.3
112.3
91.3
96.6
87.6
99.9
- Data not available.
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
Monthly Labor Review
September 1995
103
Current Labor Statistics:
International Comparisons Data
46. Unem ploym ent rates, approxim ating U.S. concepts, in nine countries, quarterly data
seasonally adjusted
Annual average
1994
1993
1995
Country
1993
1994
I
II
III
IV
II
I
United States' ......................................
Canada .................................................
Australia...............................................
Japan ....................................................
6.8
11.2
10.9
2.5
6.1
10.4
9.7
2.9
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
2.9
France ..................................................
Germany ..............................................
Italy2 .....................................................
Sweden ................................................
United Kingdom ...................................
11.9
5.8
10.3
9.3
10.5
12.7
6.5
11.4
9.6
9.6
12.3
6.2
11.0
9.8
10.1
12.7
6.4
11.0
9.8
9.9
12.7
6.5
11.6
9.7
9.7
12.7
6.5
11.1
9.7
9.5
12.6
6.5
11.8
9.3
9.0
12.5
6.5
12.2
9.3
8.7
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 Quarterly rates are for the first month of the quarter.
Break in series beginning in 1993.
- Data not available.
104
IV
Monthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
September 1995
5.7
9.5
8.4
3.2
_
-
12.2
9.4
-
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: Em ploym ent status of the w orking-age population, approxim ating U.S. concepts, 10
countries
(Numbers in thousands)
Employment status and country
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
115,461
13,123
7,300
58,820
23,620
28,020
21,800
6,250
4,418
27,210
117,834
13,378
7,588
59,410
23,760
28,240
22,290
6,380
4,443
27,380
119,865
13,631
7,758
60,050
23,890
28,390
22,350
6,500
4,437
27,720
121,669
13,900
7,974
60,860
23,980
28,610
22,660
6,530
4,494
28,150
123,869
14,151
8,228
61,920
24,170
28,840
22,530
6,640
4,552
28,420
124,787
14,329
8,444
63,050
24,300
29,410
22,670
6,770
4,597
28,540
125,303
14,408
8,490
64,280
24,490
29,760
22,940
6,870
4,591
28,450
126,982
14,482
8,562
65,040
24,600
30,040
22,910
6,970
4,520
28,400
128,040
14,663
8,619
65,470
24,710
29,960
22,570
7,070
4,443
28,310
131,056
14,832
8,776
65,780
24,970
29,840
22,450
64.8
65.8
61.6
62.3
56.9
54.7
47.2
55.5
66.9
62.1
65.3
66.3
62.8
62.1
56.9
54.9
47.8
56.0
67.0
62.1
65.6
66.7
63.0
61.9
56.7
55.0
47.6
56.3
66.4
62.5
65.9
67.2
63.3
61.9
56.4
55.1
47.4
56.1
66.9
63.2
66.5
67.5
64.0
62.2
56.1
55.2
47.3
56.5
67.3
63.6
66.4
67.3
64.6
62.6
55.6
55.0
47.2
56.8
67.0
63.7
66.0
66.7
64.1
63.2
55.6
55.4
48.6
57.5
66.6
63.3
66.3
65.9
63.9
63.4
55.9
55.1
48.5
57.9
65.3
62.9
66.2
65.5
63.6
63.3
55.7
54.5
48.3
58.6
64.2
62.8
66.6
65.3
63.9
63.1
56.0
107,150
11,742
6,697
57,260
21,150
26,010
20,490
5,650
4,293
24,150
109,597
12,095
6,974
57,740
21,240
26,380
20,610
5,740
4,326
24,300
112,440
12,422
7,129
58,320
21,320
26,590
20,590
5,850
4,340
24,860
114,968
12,819
7,398
59,310
21,520
26,800
20,870
5,920
4,410
25,730
117,342
13,086
7,720
60,500
21,850
27,200
20,770
6,070
4,480
26,350
117,914
13,165
7,859
61,710
22,100
27,950
21,080
6,260
4,513
26,550
116,877
12,916
7,676
62,920
22,140
28,480
21,360
6,380
4,447
25,930
117,598
12,842
7,637
63,620
22,010
28,660
21,230
6,470
4,265
25,520
119,306
13,015
7,680
63,810
21,780
28,220
20,240
6,450
4,028
25,340
123,060
13,292
7,921
63,860
21,810
27,900
19,890
60.1
58.9
56.5
60.6
51.0
50.7
44.4
50.1
65.0
55.1
60.7
59.9
57.7
60.4
50.8
51.3
44.2
50.3
65.2
55.1
61.5
60.8
57.9
60.1
50.6
51.5
43.8
50.7
65.0
56.1
62.3
62.0
58.7
60.4
50.6
51.6
43.7
50.8
65.7
57.8
63.0
62.4
60.1
60.8
50.7
52.0
43.6
51.7
66.2
59.0
62.7
61.9
60.1
61.3
50.5
52.2
43.9
52.5
65.8
59.2
61.6
59.8
57.9
61.8
50.3
53.0
45.3
53.4
64.5
57.7
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
49.1
51.3
43.3
53.4
58.2
56.2
62.5
58.5
57.7
61.3
48.9
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
1,990
8,426
1,492
814
1,360
2,350
1,280
1,580
490
144
2,520
9,384
1,640
925
1,420
2,590
1,380
1,680
500
255
2,880
8,734
1,649
939
1,660
2,930
1,740
2,330
620
415
2,970
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
7.0
6.7
10.4
9.6
2.1
9.6
4.3
6.9
7.1
3.1
8.9
7.4
11.3
10.8
2.2
10.5
4.6
7.3
7.2
5.6
10.1
6.8
11.2
10.9
2.5
11.9
5.8
10.3
8.8
9.3
10.5
C ivilian la b o r fo rc e
United States' .........................................................
Canada ....................................................................
Australia...................................................................
Japan .......................................................................
France .....................................................................
Germany..................................................................
Italy ..........................................................................
Netherlands..............................................................
Sweden....................................................................
United Kingdom.......................................................
-
4,418
28,310
P a rticip a tio n ra te 2
United States' .........................................................
Canada ....................................................................
Australia...................................................................
Japan .......................................................................
France .....................................................................
Germany...................................................................
Italy ..........................................................................
Netherlands..............................................................
Sweden....................................................................
United Kingdom.......................................................
-
48.0
_
63.6
62.7
E m ployed
United States’ .........................................................
Canada ....................................................................
Australia...................................................................
Japan .......................................................................
France .....................................................................
Germany...................................................................
Italy ..........................................................................
Netherlands..............................................................
Sweden....................................................................
United Kingdom.......................................................
-
3,992
25,590
E m p lo y m e n t-p o p u la tio n ra tio 3
United States' .........................................................
Canada ....................................................................
Australia...................................................................
Japan .......................................................................
France .....................................................................
Germany...................................................................
Italy ..........................................................................
Netherlands..............................................................
Sweden....................................................................
United Kingdom.......................................................
-
42.5
-
57.4
56.7
U n e m p lo y e d
United States' .........................................................
Canada ....................................................................
Australia...................................................................
Japan .......................................................................
France .....................................................................
Germany...................................................................
Italy ..........................................................................
Netherlands..............................................................
Sweden....................................................................
United Kingdom.......................................................
7,996
1,541
856
1,920
3,160
1,940
2,560
_
426
2,720
U n e m p lo y m e n t ra te
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
6.1
10.4
9.7
2.9
12.7
6.5
11.4
_
9.6
9.6
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.
Monthly Labor Review
September 1995
105
Current Labor Statistics:
48.
International Comparisons Data
Annual indexes o f manufacturing productivity and related measures, 12 countries
(1982=100)
Item and country
1960
1970
1973
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
O u tp u t p er hou r
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
123.1
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
115.8
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
U n it la b o r 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
U n it lab o r 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
United States.........................................................................................
Canada ..................................................................................................
Japan .....................................................................................................
Belgium..................................................................................................
Denmark................................................................................................
France ...................................................................................................
Germany.................................................................................................
Italy ........................................................................................................
Netherlands............................................................................................
Norway ..................................................................................................
Sweden..................................................................................................
United Kingdom.....................................................................................
O utp ut
United States.........................................................................................
Canada ..................................................................................................
Japan .....................................................................................................
Belgium..................................................................................................
Denmark.................................................................................................
France ...................................................................................................
Germany.................................................................................................
Italy ........................................................................................................
Netherlands............................................................................................
Norway ..................................................................................................
Sweden..................................................................................................
United Kingdom.....................................................................................
T o ta l hou rs
United States.........................................................................................
Canada........................... .......................................................................
Japan .....................................................................................................
Belgium..................................................................................................
Denmark.................................................................................................
France ...................................................................................................
Germany.................................................................................................
Italy ........................................................................................................
Netherlands............................................................................................
Norway ..................................................................................................
Sweden..................................................................................................
United Kingdom.....................................................................................
C o m p e n s a tio n p e r hour
- Data not available.
106
Monthly Labor Review
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
September 1995
49.
Occupational injury and illness incidence rates by industry,1 United States
Incidence rates per 100 full-time workers3
Industry and type of case2
1985
1986
1987
1988
1989’
1990
1991
1992
19934
P R IV A T E S E C T O R 5
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
-
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
-
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
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
-
Total cases................................................................................................
Lost workday ca ses..................................................................................
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
_
_
15.9
7.2
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
11.5
11.3
10.7
A g riculture, fo re s try , an d fish in g 5
Total cases................................................................................................
Lost workday ca ses..................................................................................
Lost workdays............................................................................................
M ining
Total cases...............................................................................................
Lost workday cases..................................................................................
Lost workdays...........................................................................................
C o n stru ctio n
Total cases................................................................................................
Lost workday ca ses..................................................................................
Lost workdays............................................................................................
General building contractors:
Total cases..................................................................................
. .
Lost workday ca ses..................................................................................
Lost workdays............................................................................................
Heavy construction, except building:
Total cases................................................................................................
Lost workday ca ses...................................................................................
Lost workdays............................................................................................
Special trade contractors:
Total cases................................................................................................
Lost workday cases ..................................................................................
Lost workdays............................................................................................
.
.
.
M an u factu rin g
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.............................................................................................
16.1
7.2
16.9
7.8
_
.
.
.
.
.
.
.
_
See footnotes at end of table.
https://fraser.stlouisfed.org
Federal Reserve Bank of St. Louis
Monthly Labor Review
September 1995
107
Current Labor Statistics:
Injury and Illness Data
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
1987
1988
19891
1990
1991
1992
19934
4.4
77.6
4.6
82.3
5.1
93.5
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
5.1
2.3
38.8
6.3
2.7
49.4
7.0
3.1
58.8
7.0
3.3
59.0
7.0
3.2
63.4
6.5
3.1
61.6
6.4
3.1
62.4
6.0
2.8
64.2
5.9
2.7
5.1
2.4
49.9
7.1
3.2
67.5
7.3
3.1
65.9
7.0
3.2
68.4
6.6
3.3
68.1
6.6
3.1
77.3
6.2
2.9
68.2
5.9
2.8
71.2
5.2
2.5
13.4
6.3
107.4
14.0
6.6
118.2
15.9
7.6
130.8
16.3
8.1
142.9
16.2
8.0
147.2
16.2
7.8
151.3
15.1
7.2
150.9
14.5
6.8
153.3
13.9
6.5
-
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
12.1
5.4
128.5
12.1
5.5
-
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
■
-
-
-
-
-
-
T ra n s p o rta tio n an d public utilities
Total cases................................................................................................
Lost workday cases ..................................................................................
Lost workdays ..........................................................................................
W h o le s a le and retail tra d e
Total cases................................................................................................
Lost workday cases ..................................................................................
Lost workdays............................................................................................
Wholesale trade:
Total cases................................................................................................
Lost workday ca ses..................................................................................
Lost workdays............................................................................................
Retail trade:
Total cases................................................................................................
Lost workday cases ..................................................................................
Lost workdays............................................................................................
Finance, insurance , and real e s ta te
Total cases................................................................................................
Lost workday ca ses..................................................................................
Lost workdays............................................................................................
S e rv ic e s
Total cases................................................................................................
Lost workday ca ses..................................................................................
Lost workdays............................................................................................
1 Data for 1989 and subsequent years are based on the S ta n d a rd
1987 Edition. For this reason, they are not
strictly comparable with data for the years 1985-88, which were based on the
S ta n d a rd In d u s tria l C la s s ific a tio n M a n u a l, 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:
In d u s tria l C la s s ific a tio n M a n u a l,
108
Monthly Labor Review
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Federal Reserve Bank of St. Louis
September 1995
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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Schedule of release dates fo r B L S statistical series
Period
covered
Series
Release
date
Employment situation
September 1
August
Septem ber/
2ndquarter
Release
date
Period
covered
Release
date
Period
covered
MLR table
number
October 6
September
November3
October
1; 4-20
Productivity and costs:
Nonfinancial corporations
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Nonfarm business and manufacturing
3rdquarter 2; 42-45
Producer Price Indexes
September 12
August
October 12
September
November 9
October
2; 34-36
Consumer Price Indexes
September 13
August
October 13
September
November 15
October
2; 31-33
Real earnings
September 13
August
October 13
September
November 15
October
13-16
Employment Cost Indexes
October 31
3rdquarter
1-3 ; 21-24
Major collective bargaining settlements
October 31
3rdquarter
3; 26-29
U.S. Import and Export Price Indexes
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Novem ber/
September 29
August
November 1 September
November 30
October
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