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OCR for page 91
~ Occupational Sex Segregation:
U Prospects for the 1980s
ANDREA H. BELLER and
KEE,OK KIM HAN
Occupational segregation declined 2 to 3
times as rapidly during the 1970s as during
the 1960s (Belier, in this volume). While
this is encouraging, segregation continues
at a high level overall; as of 1981, 61.7 per-
cent of women (or men) would stir] have to
change occupations for the occupational dis-
tribution to become completely integrated
by sex (Belier, in this volume). What pros-
pects lie ahead for the remainder of this
decade? To attempt to answer this question,
we shall make several projections of occu-
pational segregation to 1990. These projec-
tions are based on the trends in segregation
analyzed and reported in Beller (in this vol-
ume).
The best measure of occupational segre-
gation, the segregation index, is computed
as follows:
St = i/2~ | m`'—fit | ~
where m`' is the percentage of the male labor
force employed in occupation i in year t,
end fi' is the percentage of the female labor
force employed in occupation i in year t.
The index may take on a value between
0 and 100, where 0 represents perfect in-
tegration and 100, complete segregation. Ike
number tells the proportion of women (or
of men) that would have to be redistributed
among occupations for the occupational dis-
tribution to reach complete equality be-
tween the sexes.
ASSUMPTIONS, DATA, AND
METHODOLOGY
In order to project the index of segrega-
tion, we need to know the projected distri-
bution of employment across occupations and
the projected sex composition within each
occupation. Occupational employment pro-
jections for 1990, constructed by the Bureau
of Labor Statistics (BLS), are published in
Volume 2 of The National Industry-Occu-
pation Employment Matrix (Department of
Labor, BLS, 1981~. These projections are
(1) based upon the bureau's intermediate labor
force projections and assume a 4.5 percent
unemployment rate in 1990. These projec-
tions are discussed further in Appendix A.
In constructing projections on the sex
composition within occupations, we employ
a number of techniques and entertain a va-
riety of alternative assumptions. The basic
91
OCR for page 92
92
ANDREA H. BELLER AND KEE-OK KIM HAN
.
assumption underlying most of these pro-
jections is that the sex composition of all
occupations or of each occupation individ-
ually continues to change during the 1980s
along the path established during the 1970s.
The data on which we base our projections
come from the Current Population Survey
(CPS), collected monthly by the Bureau of
the Census either from the March Annual
Demographic File (ADF) or from the un-
published annual averages (AA) computed
by BLS from the monthly data. First, we
make three projections based upon infor-
mation about the labor force as a whole,
employing linear and logistic models. Then
we make four projections based upon infor-
mation for age cohorts; the equations are
specified according to the linear spline model.
All of these projections are based upon 255
3-digit census occupations.
Linear Group Labor Force Projection (P1)
First, as in Blau and Hendricks (1979),
we assume that the sex composition in all
occupations changes over time according to
the same linear function. We estimate an
equation in which the proportion of males
in each occupation in 1981 is a linear func-
tion of the proportion of males in that oc-
cupation in 1972, of the percentage change
in employment in that occupation over the
period, and of the interaction between the
proportion of males and the percentage
change in employment. Using the AA data,
the following equation is estimated:
Pi,s~ = a + ~P`,72 + ~Y6Ei,s~-72
+ 8(P`,72 * ~Ei~s~-72) + e`, (2)
where Pi,' is the percentage of males in oc-
cupation i in year t = 1972 or 1981, and
AEi,~_72 is the percentage change in em-
ployment in occupation i between 1972 and
1981.
This mode! has a logical rationale. The
proportion of males in an occupation de-
pends on the initial proportion of males as
well as on the growth in the occupation over
the period. It is easier for women to enter
growing occupations than to enter stable or
declining ones. Moreover, the effect of the
initial proportion on the present proportion
might depend on the growth rate of the oc-
cupation. Ibis model also has some draw-
backs. Because it averages over all occu-
pations, it will overestimate change in some
occupations and underestimate change in
others. Because it is linear rather than lo-
gistic, the projected values for the propor-
tion of males could exceed 1.0 or be nega-
tive.
To eliminate the effects of averaging, in
our two other labor force projections we as-
sume that each occupation's sex composition
is a function of time.
Linear Individual Labor Force Projection
(P2)
First, we specify the percentage of males
in each occupation as a linear function of
time:
p' = a + bt + e`, (3)
where t is 1,2, . . .11 for years = 1971 to 1974,
1977, and 1981.i But, since pi is a fraction
between O and 1, the linear function might
not be a good model, particularly near the
extremes.
~ Eqs. (3) and (5) require a time series data set. Data
for 1971 to 1974 and 1977 are from the Annual De-
mographic Files (ADF) of the monthly CPS, while 1981
data are from the unpublished BES annual averages of
the monthly CPS. The former are the only years for
which we have the ADF, while the latter is the most
recent year of data available. The AA data are somewhat
more reliable statistically than are the monthly data.
Eq. (2), which requires data only for the end points,
is estimated with AA data alone, since we can remain
within a single, statistically more reliable data set.
OCR for page 93
OCCUPATIONAL SEX SEGREGATION: PROSPECTS FOR THE 1980s
.
93
Logistic Individual Labor Force Projection
(P3)
The logistic equation constrains the value
of pi to lie between 0 and 1:
eta
where ,B is a vector of parameters to be es-
timated, and t is the year as above. Eq. (4)
can be rewritten in the "log odds ratio" form:
(l—Pt)
This equation, which can be estimated by
ordinary least squares (OLS), will have het-
eroscecIastic residuals, increasing the stand-
ard errors; however, this is not important
for purposes of prediction.2
A different approach to projecting the
segregation of the work force in 1990 is to
piece together information about population
subgroups. Beller (in this volume) examined
occupational segregation by work experi-
ence cohort and found that (1) new entrants
into the labor market are less segregated
than is the rest of the labor force, and (2)
between 1971 and 1977, occupational seg-
regation declined for the entering cohort as
it aged and between entering cohorts.
Changes in occupational segregation can be
projected by cohort and aggregated to the
labor force. In order to accomplish this, we
need to know the age-sex specific compo-
sition of the civilian labor force in 1990; for-
tunately it has been projected by the BLS
(Department of Labor, BLS, 19791. Since
we do not have the additional data for 1990
2 This equation should be modified to include an
equation error, interpreted as a surrogate for omitted
variables, in addition to the usual error term. We will
assume that the variance of the equation error equals
0, as discussed in Medoff~1979~. In his empirical results
the estimates of the equation modified to include equa-
tion error were not much different from those that were
not.
needed to identify work experience cohorts,
we make our projections based upon age
cohorts. We project to 1990 the sex com-
position of individual occupations for each
age group. Then we use the BLS projections
on cohort size to aggregate over groups and
(4) to obtain the sex composition of each oc-
cupation for the labor force as a whole. Com-
bining these with the BLS occupational em-
ployment projections, we compute the
projected segregation index. The details of
this approach are described in Appendix A.
The advantage of using these projection
methods is that we can incorporate specu-
lations about what might happen under al-
ternative scenarios for such factors as federal
efforts on affi~-~ative action. The disadvan-
tage is that projections for specified small
subgroups of a population are likely to be
less reliable than are projections for the whole
population. We make four projections based
upon age cohorts: conservative, moderate,
moderately optimistic, and optimistic.3 All
cohort projections are based upon trends
between 1971 and 1977 only; the latter is
the most recent year for which we have the
ADF data containing the demographic de-
tai} to identify age cohorts.
Conservative Age Cohort Projection (P5)
The conservative projection assumes that
no further change occurs for a given cohort
after 1977, partly because equal employ-
ment opportunity (EEO) efforts have slowed
down. Each cohort maintains the same sex
composition within occupations as it ages,
and the youngest cohort (16 to 24 years of
3 The assumptions about behavior and policy under-
lying each of these projections do not generate the
particular mathematical models we use. Rather the
models postulate change as a linear function of time,
since affirmative action policies and related behavior
have changed over time. More complex mathematical
models might also be consistent with the underlying
assumptions about change.
OCR for page 94
94
ANDREA H. BELLER
~ KEE-OK KIM
age) has the same occupational sex compo-
sition in 1990 as in 1977:
P`,j+ ~ (1990) = P`,j (1977), (6)
and
P$,1 (1990) = Pi,1 (1977), (7)
where j is age cohorts 1 to 5, defined by the
age groups in the 1990 BLS projections,
shown in Appendix A.
The assumption of no further change for
an individual cohort need not imply no change
for the labor force as a whole as long as
younger cohorts are less segregated than older and
ones are. As the labor force ages, younger,
less segregated cohorts replace older, more
segregated ones. Nonetheless, the assump-
tion of no change for all cohorts after 1977
is quite conservative in light of the decline
in segregation through 1981 shown by the
aggregate labor force data (Belier, in this
volume, Table 2-11. Thus, these conserva-
tive assumptions may be viewed as yielding
a lower-bound estimate on the projected de-
cline in the index of segregation during the
1980s.
Moderate Age Cohort Projection (P6)
The moderate projection is constructed
under the assumption that the rate of change
in the sex composition of occupations for the
youngest (entering) cohort will be the same
between 1977 and 1990 as it was between
1971 and 1977 a period of considerable
change. We might expect this if youthful
attitudes and aspirations have changed, but
equal opportunity efforts subside so that, as
it becomes older, the rest of the labor force
remains as segregated as it was in 1977. This
projection applies Eq. (6) to older cohorts
and projects change for the youngest cohort
according to a linear spline function esti-
mated on 1971 and 1977 data. The linear
spline allows different segments of a contin-
uous linear function to have different slopes
(Poirier, 19761. It is likely that the sex com-
position of highly male (more than 85 per-
cent male) and highly female (less than 15
percent male) occupations will change at dif-
ferent rates than will occupations with sex
compositions in between. We estimate the
following equation:
Pi,~41977) = al + ,3~pi,~41971)
+ ~y~Fi,~1971) + 8,.M`,~1971) + al, (8)
where
Fin = 0.00ifpi,~ = 0.15tol.00,
Fi,~ = 0.15—pa, if pa < 0.15,
MA = 0.00 if Pi,, = 0.00 to 0.85,
Mi,~ = pa,—0.85 if pa > 0.85.
This equation is estimated for a six-year
period, 1971 to 1977, and thus can be used
to predict the value of pi,lkl983) using 1977
data for the independent variables. The 1977-
1983 growth rate in the proportion of males
in occupation i for this cohort can then be
used to predict pi,,fl9901.
Optimistic and Moderately Optimistic Age
Cohort Projections (P8 and P7)
The optimistic projection (P8) is con-
structed under the assumption that affirm-
ative action, attitudes, and other factors con-
tinue to change during the 1980s at the same
rate as during the 1970s. Actually, this is
quite optimistic given what we already know
about the Reagan administration's proposed
cutbacks in affirmative action and de-em-
phasis on enforcement. Thus, we consider
this to be an upper-bound estimate on how
much change could occur under the best of
circumstances. For P8, we assume that as
each 1977 cohort ages to 1990 its rate of
change in percentage of males in each oc-
cupation is the same as for the similar cohort
as it aged between 1971 and 1977, and that
the rate of change between entering cohorts
in 1977 and 1990 is the same as between
entering cohorts in 1971 and 1977. For these
OCR for page 95
OCCUPATIONAL SEX SEGREGATION: PROSPECTS FOR THE 1980s
. . .
95
projections, we apply Eq. (8) to the young-
est cohort and estimate the following equa-
tion for ogler cohorts:
P`,j+ ~1977) = of + ,Bjp`,j(1971)
+ ~yjF`,j(1971) + ~yMi,j(1971) + A. (9)
If the mechanisms have been put into place,
then Reagan's policies may succeed only in
reducing but not in eliminating change. We
consider it moderately optimistic (P7) to as-
sume that the rate of change for each cohort
during the 1980s is one-half the rate during
the 1970s. The value of P`,j+1~1983) provides
We moderately optimist/c projection, P7, and
the value of Pi,j+141990), the optimistic pro-
jection, P8.
PROjECTIONS OF OCCUPATIONAL
SEGREGATION, 1981 TO 1990
Segregation indexes computed using BLS
occupation projections and our linear pro-
jections on the sex composition of occupa-
tions for the labor force yield only a modest
decline in occupational segregation between
1981 and 1990. As shown in Table 6-1, col-
umn 1, the segregation index is projected
to decline by 1.69 percentage points to 59.97
TABLE 6-1 Actual and Projected Segregation Indexes, 1972, 1977, 1981, and 1990
Employment
Year Unstandardized Standardized
. . ..
1972 68.32 67.23
1977 64.15 64.02
1981 61.66 61.66
1990
Labor force
Linear-group (P1) 59.97 59.35
Linear-individual (P2) 60.37 59.51
Logistic-individual (P3) 56.06 55.20
Combined-individual (P4) 59.91 59.03
Age cohort
Conservative (P5) 62.11 60.89
Moderate (P6) 57.29 56.02
Moderately optimistic (P7) 50.02 49.09
Optimistic (P8) 42.20 41.33
NOTES: PI was computed based on the following equation for projecting percentage of males in occupation i:
Pi,81 = - ·016 + ·970 P`72 - ·036^ E`.8l_72 - ·042 (Pi72 *^E`8~_72),
(1.65) (75.61) (1.64) (1.36)
R2 = .966, N = 262, t-values in parentheses.
P2 and P3 were computed based upon separate linear or logistic equations for each occupation, respectively.
P4 was computed by selecting the equation for each occupation with the highest R2 if either functional form was
significant; if neither was significant assuming the 1981 value. P5 assumes no further change after 1977 in the
percentage of males in each occupation for each age cohort; P6 assumes no change for all but the youngest cohort,
which experiences a linear change for all but the youngest cohort, which experiences a linear rate of change; P7
assumes a linear rate of change of percentage of males in each occuaption for each age cohort at one-half the rate
during the 1970s; P8 assumes a linear rate of change at the same rate as during the 1970s. Employment standardized
indexes are standardized to 1981 employment totals. Projected segregation indexes include only 255 occupations
because the BLS employment projections were unavailable for 7 of the occupations included in the analysis of
trends in Beller (in this volume).
SOURCES: Annual Demographic Files of Current Population Survey, 1972 to 1975 and 1978, computer tapes;
and Bureau of Labor Statistics, annual averages of monthly Current Population Surveys, 1972, 1977, and 1981,
unpublished tabulations.
OCR for page 96
96
ANDREA H. BELLER AND KEE-OK KIM HAN
or by 1.29 percentage points to 60.37 ac-
cording to the linear-group (P1) and linear-
individual (P2) projections, respectively.
These projected rates of decline in the over-
all index are much slower than during the
past decacle. A logistic rate of growth (P3)
in the sex composition of individual occu-
pations combines with the BLS occupation
projections to predict a decline in the seg-
regation index from 61.66 in 1981 to 56.06
in 1990. This projected 5.6 percentage point
decline is around 84 percent of the actual
6.66 percentage point decline between 1972
and 1981.
To decompose these changes, we stand-
arclize the projected segregation indexes to
the 1981 occupational distribution.4 Shown
in column 2, the employment standardized
segregation indexes lie slightly below the
unstandardized indexes indicating that the
occupational `distribution is projected (by the
BLS) to change slightly toward more seg-
regated occupations between 1981 and 1990.
This contrasts with the slight change in the
occupational distribution toward less seg-
regated occupations during the 1970s. The
projected employment standardized segre-
gation index based upon logistic trends (P3)
declines by 6.46 percentage points cluring
the 1980s to 55.20, or by more than the 5.57
percentage point decline in the standard-
or by 1.29 percentage points to 60.37 ac-
4 1he employment standardized index of segregation
is defined as follows:
where
S`* = 1/22 ~ m* - ~ I,
(MtiTtt) (Ttt-l) (1~)
2(Mt/Ttt) (T,'_1)
(FATE`) (Ttt-l) (1~)
(FtiTtt) (Tit-l)
F`t is the number of females in occupation i in year t,
M`' is the number of males in occupation i in year t,
and T`' equals F.`' + M`' equals total employment in
occupation i in year t.
cording to the linear-group (P1) and linear-
izec! index during the 1970s. Thus, accord-
ing to logistic trends, changes in the sex
composition of occupations toward a less
segregated work force will be larger during
the 1980s than during the 1970s; however,
projected adverse changes in the occupa-
tional distribution will more than offset these
more favorable changes in sex composition.
From these data we conclude that projected
changes in the sex composition of occupa-
lions during the 1980s based upon changes
between 1971 and 1981 will decrease oc-
cupational segregation less than in the past
in part because of opposing changes in the
occupational distribution toward increased
segregation.
However, these projections of occupa-
tional sex composition may be somewhat off,
because they project the female share of the
labor force in 1990 as higher than the BLS
projects them (Department of Labor, BLS,
1979, Table 5, p. 71. The BLS projects the
female share of the labor force to grow from
41.0 in 1977 to 45.5 in 1990, whereas PI
projects the female share (aggregated from
occupational shares) to be 49.3 in 1990, P2
projects it to be 48.2, and P3 projects it to
be 50.3. Since projections for a population
(the labor force) tend to be more accurate
than projections for a specified subset of that
population (occupations), the BLS projec-
tions suggest that our own projections some-
what overestimate the female share of the
labor force in 1ggo.s
What, then, do these projections tell us?
The sex composition of some occupations
changed so rapidly during the 1970s that the
rate cannot be sustained during the 1980s
on the basis of projected growth in the fe-
male labor force. For which subset of oc-
cupations will the female rate of entry de-
cline during the 1980s? Will it decline further
5 This difference may be somewhat mitigated by the
fact that the BLS has consistently underestimated the
growth rate of the female labor force (Lloyd and Niemi,
1979, p. 311, n. 19; Smith, 1977, p. 23~.
OCR for page 97
OCCUPATIONAL SEX SEGREGATION: PROSPECTS FOR THE 1980s
97
in the large, traditionally female occupations
so that not only will the proportion of the
female labor force that is in them decline,
but also the female proportion of these oc-
cupations will decline? If so, occupational
segregation will decline more than is pro-
jected. Or will it decline in the traditionally
male occupations to which access has been
increased so recently? If so, occupational
segregation will decline less than is pro-
jected. Obviously incentives can be created
by public policy for movement in one di-
rection or the other. If affirmative action
continues to promote equal opportunity for
women in nontraditional occupations, then
traditionally female occupations will be-
come relatively less attractive. If opportu-
nities decline in nontraditional jobs, then
female occupations will look relatively more
attractive. As our experience during the 1970s
suggests, federal policy can significantly af-
fect occupational segregation (Belier,
1982a,b).
Each of these projection methods has ad-
vantages and disadvantages, and each makes
projections that are quite reasonable for many
individual occupations. The projected fe-
male percentages of PI to P3, as well as the
estimated annual linear trend of P2, are pre-
sented in Appendix B. Table B-1. As these
data show, the logistic growth model, P3,
does very well in capturing the acceleration
or deceleration in the rate of change in per-
centage of females near the tails of the dis-
tribution; however, it overprotects the fe-
male share of the labor force the most. Ike
linear-individual projection, P2, overpro-
jects the female share the least. Since the
truth probably lies somewhere in between,
we construct a combined estimate. For each
occupation we choose the individual equa-
tion with the highest R2, where at least one
is significant at the 10 percent level accord-
ing to the F-statistic. Where neither the lin-
ear nor the logistic equation is significant,
we assume that no change occurs in percent
female between 1981 and 1990. As shown
in Table B-1, while the majority of occu-
pations shows no significant trend in the
percent female, more than one-fourth, 27.5
percent, shows a significant increase. These
assumptions yield the combined-individual
projection (P4) of the segregation index of
59.91, only slightly below P2.
MAjOR COMPONENTS OF PROJECTED
CHANGE IN THE INDEX
Many of the trends toward decreasing
segregation begun in the 1970s (Belier, in
this volume) are projected to continue into
the 1980s. However, counterbalancing these
will be a major new source of increasing
segregation. According to the P2 linear pro-
jections, a number of predominantly male
crafts and operative and laborer occupations
are projected to grow (some rapidly) and to
account for increasing proportions of the male
labor force during the 1980s. According to
the PI linear projections, if women take a
larger share of the growth in these jobs as
they did in the male occupations that grew
rapidly during the 1970s, then these occu-
pations may not increase overall segrega-
tion. Several traditionally female occupa-
tions are projected to continue to account
for decreasing proportions of the female la-
bor force, while some increase in segrega-
tion will result from the expansion of the
predominantly female health services oc-
cupations.
According to P2, occupations projected to
continue contributing to declines in the seg-
regation index during the 1980s are ele-
mentary school teachers; telephone opera-
tors; cooks, except private household; child
care workers, private household; and maids
and servants, private household. Declines
in the segregation index during the 1980s
are projected from some new sources as well:
secondary school teachers; managers and
administrators, not elsewhere classified;
bookkeepers; waiters; and hairdressers and
cosmotologists. Also projected to decrease
the segregation index during the 1980s are
two female occupations registered nurses
OCR for page 98
98
ANDREA H. BELLER AND KEE-OK KIM HAN
and bank tellers that increased it during
the 1970s.
The occupation of miscellaneous clerical
workers is projected to continue increasing
the segregation index by a large amount.
Also projected to increase the index during
the 1980s is the rapidly growing secretarial
occupation, which decreased it during the
1970s. Several female health services oc-
cupations are projected to grow and to be-
come more segregated: health aides, nurs-
ing aides, and practical nurses.6
As mentioned before, the biggest change
projected for the 1980s that will hinder fur-
ther declines in occupational segregation is
substantial growth in a number of highly
male crafts and operative and laborer oc-
cupations. The following occupations, with
the projected percentage of females in pa-
rentheses, will add a large amount to the
1990 segregation index if their female per-
centage grows during the 1980s at the same
linear rate as during the 1970s: carpenters
(3.0 percent); auto mechanics (0.7 percent);
heavy-equipment mechanics (2.8 percent);
welders and flame-cutters (5.3 percent); ma-
chine operatives, miscellaneous (27.7 per-
cent); truck drivers (4.0 percent); and con-
struction laborers (4.5 percent). Of these,
women made significant inroads during the
1970s only into the occupations of carpen-
ter, heavy-equipment mechanic, and truck
driver. In all except machine operatives, the
percentage of females is projected to grow
between 1981 and 1990, but by nearly im-
perceptible amounts. However, growth in
these occupations need not hinder declines
in occupational segregation; if these male
blue-collar occupations respond to growth
in the same way as the male white-colIar
occupations did during the 1970s, allocating
a higher share of new than of existing jobs
6 These occupations were identified on the basis of
the linear trends for each individual occupation; they
carry the assumption that the percentage of females
during the 1980s follows the same trend as during the
1970s regardless of any changes in total occupational
employment that might occur.
to women, the PI projections show that the
percentages of females could increase among
carpenters (to 8.3 percent); auto mechanics
(to 6.8 percent); heavy-equipment mechan-
ics (to 9.4 percent); welclers and flame-cut-
ters (to 11.2 percent); machine operatives,
miscellaneous (to 34.1 percent); truck driv-
ers (to 9.2 percent); and construction labor-
ers (to 9.1 percent). Increasing the rate at
which women enter those blue-collar oc-
cupations that are projected to grow during
the coming decade should be a major focus
of any public policy designed to reduce oc-
cupational segregation.7
PROJECTIONS BASED ON AGE COHORTS
The four segregation indexes based upon
projections of occupational sex composition
within age cohorts vary considerably de-
pending upon the assumptions. Based upon
conservative assumptions, P5 projects only
a slight decline in the index of segregation,
from 64.15 in 1977 to 62.11 in 1990, slightly
above the actual 1981 index. (The projected
indexes for each age cohort, as well as the
indexes for 1971 and 1977, appear in Ap-
pendix B. Table B-2.) Note that these con-
servative assumptions yield a projection only
slightly above P1, P2, and P4. The con-
servative projection appears especially so in
light of the actual 1981 segregation index.
Based upon moderate assumptions that
further declines occur only for the youngest
cohort after 1977, P6 projects a decline in
the index of segregation to 57.29 in 1990,
closest to the logistic projection, P3, of 56.06.
(P6 projects a female share of the labor force
of 48.3 percent in 1990.) While the linear
spline equation predicts a substantial drop
7 Whether this projected growth in blue-collar jobs
will be realized is questionable because of the present
high unemployment rate contrasted with the 4.5 per-
centage rate embedded in the BES occupation projec-
tions for 1990. Moreover, as Carey (1981, p. 42) points
out, job growth in blue-collar occupations is more sen-
sitive to the underlying assumptions of the projections
than in other major occupational categories.
OCR for page 99
OCCUPATIONAL SEX SEGREGATION: PROSPECTS FOR THE 1980s
in segregation for the youngest cohort (see
Table B-2), even changes of substantial mag-
nitude restricted to a single cohort have a
limited impact on the overall index. It would
take many years of a continued influx of less
segregated cohorts for the overall occupa-
tional distribution to show a major decline
in segregation.
The moderately optimistic and the opti-
mistic age cohort projections, P7 and P8,
depart from the others in projecting a sig-
nificant decline in the index of segregation
during the 1980s. Based upon the assump-
tion that the total change in percentage of
males for each occupation as a cohort ages
between 1977 and 1990 is the same as for
the similar cohort between 1971 and 1977,
i.e., one-half the rate of change, P7 projects
the index of segregation overall to decline
by 11.68 percentage points to 50.02 in 1990.
P7 projects the female share of the labor
force at 47 percent, which is close to the
BLS projection of 45.5. Projection P8 is very
optimistic and assumes that the rate of change
in percentage of males by occupation for
each cohort between 1977 and 1990 is the
same as between 1971 and 1977 for the com-
parable cohort, i.e., double the total change.
P8 predicts a rather substantial drop in the
segregation index of nearly 20 points to 42.20
and projects a female share of the labor force
just over 50 percent.
The age cohort projections differ from the
labor force projections in their emphasis upon
source of change. They assume that segre-
gation is a characteristic of cohorts of indi-
viduals rather than of occupations or of the
labor force. Thus, change is based more upon
the characteristics of the supply side of the
labor market than, as in the earlier projec-
tions, upon the demand side. If, on the one
hand, segregation were primarily the result
of the choices of each sex, then the opti-
mistic projections suggest that occupational
segregation could decline significantly dur-
ing the 1980s. If, on the other hand, seg-
regation were primarily the result of em-
ployer practices and other demand-side
factors, modest Farther declines are pre-
99
dieted for the 1980s. The truth may well lie
in between. In the next section, we focus
on changes in the characteristics of the sup-
ply side of the professional labor market.
PROJECTIONS TO 1990 OF SEGREGATION
AMONG PROFESSIONAL OCCUPATIONS
BASED ON COLLEGE MAjORS
In our final set of projections on segre-
gation among professional occupations we
break with previous methodological pat-
terns. So far we have projected trends in
the sex composition of occupations either for
the whole labor force or for a subgroup of
that population. Here we use an aggregate
time series regression framework in which
the segregation indexes are variables. Since
professional occupations generally require a
college degree, segregation among profes-
sional occupations is hypothesized to be a
function of segregation by college field of
study among recent bachelor's degree re-
cinients. As long as the sexes face equal op-
portunity in the job market, to the extent
that a greater similarity arises in the edu-
cational preparation of men and women,
segregation in professional occupations should
decline. We have chosen to specify a rela-
tionship where segregation in professional
occupations in year t is a function of seg-
regation in college majors in year t—3, a lag
of three years. While many of last year's
college graduates fill this year's job vacan-
cies, several previous years' graduates may
also, especially where postgraduate educa-
tion or training is involved.8 We thus specify
the following equation:
S`° = a + ~ St_3 + e`, (10)
where S° is the index of segregation among
8 We postulate a relationship for a single year, be-
cause the number of years for which we have compa-
rable time series data is limited. If more years of data
were available, a more complex distributed-lag model
in which occupational segregation in year t was a func-
tion of several previous years of segregation among
college graduates might be desirable.
OCR for page 100
100
professional occupations in year t, St_3 is
the index of segregation among bachelor's
degree recipients by major field of study in
year t—3, and t is 1974 to 1981.
Ike data on the size and sex composition
of college majors are taken from the National
Center for Education Statistics' (NCES, 1980)
Projections of Eclucation Statistics to 1988-
89, and the data for professional occupations
are from the published AA data (Employ-
ment and Earnings, various issues). The
model and data are discussed in more detail
in Appendix C.
First, we computed a time series of seg-
regation indexes for college major among
bachelor's degree recipients and for profes-
sional occupations, which appear in Table
6-2, columns (1) and (2), respectively. With
these data we estimate Eq. (101; the esti-
mated equation with t-values in parentheses
· 9
S:
SO _
t —
23.88 + 0.727 St—3
(23.50) (29.20) (11)
R2 = 0.99, N = 8.
Initially we used the NCES projections
of the number of female and male college
graduates by fielc! of study through 1989
(NCES, 1980, pp. 66-71) to compute pro-
jected segregation indexes for college ma-
jors, as shown in Table 6-2, column (3). In
contrast to the increasingly rapid decline in
segregation among college majors during the
1970s (column [14), the NCES projections
show a slight increase in segregation in 1979
and only a modest decline thereafter (col-
umn f31). Then, using Eq. (11), we com-
puted the projected segregation indexes for
professional occupations, which appear in
column (4). Likewise, the projected segre-
9 We also estimated this equation for 1-, 2-, 4-, and
5-year lags, and found the explanatory power greatest
for the 3-year lag. Given the linear trend in the data,
a 3-year lag is approximately equivalent to a S-year
moving average.
ANDREA H. BELLER AND KEE-OK KIM HAN
cation indexes for professional occupations
increase (in 1982) and then decline very
slowly thereafter. In fact, the projected seg-
regation index for professional occupations
of 48.36 in 1990 based on the NCES pro-
jections lies only slightly below the actual
1981 index 49.61. This value is slightly
above one for professional occupations com-
puted with the earlier combined-individual
projection (P4), 47.05. We suspect from the
distinct break in the series between 1978
and 1979 that the NCES projections under-
estimate the extent of change in the sex com-
position of college majors. is
Assuming that the number of majors by
field has been correctly projected by NCES
but that the sex composition has not, we
estimate the trend in the sex composition
for each college major as a linear function
of time and then project it into the future.
We estimate equations of the following form
for each major field:
PF' = a + fit + e`, (12)
where PF' is the percentage of females among
bachelor's degree recipients in a major field
in year t, t = 1969 to 1978, and ,B is the
estimated trend.
The estimated trends in percentage of fe-
males by major field of study are presented
in Appendix B. Table B-3, along with the
actual 1969 and 1978 values and the pro-
jected 1989 values. These estimates reveal
two major trends among college students:
a To check this we computed the actual segregation
index among college fields of study of bachelor's degree
recipients for 1979-1980 directly from data from Earned
Degrees Conferred 1979-80 (NCES, 1981~. (The cate-
gories used for 1978-1979 data were not comparable
with those published in the NCES projections volume.)
The actual index for 1980 was 34.53, below that based
upon NCES projections. While these data are not strictly
comparable with earlier data, because the NCES sup-
plemented the data from Earned Degrees Conferred
with information from additional sources (NCES, 1980,
p. 49), they are nevertheless suggestive.
OCR for page 101
OCCUPATIONAL SEX SEGREGATION: PROSPECTS FOR THE 1980s
Z01
TABLE 6-2 Actual and Projected Segregation Indexes for College Majors and
Professional Occupations
Actual Projection I Projection II Projection III
College
Majors
Year (1)
1969 46.08
45.45
44.56
44.17
43.32
41.99
40.42
38.77
36.92
35.62
Professional
Occupations
(2)
College
Majors
(3)
Professional
Occupations
(4)
College
Majors
(5)
Professional
Occupations
(6)
College
Majors
(7)
Professional
Occupations
(8)
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
58.94
56.13
56.11
55.58
54.07
53.32
51.98
34.04 50.98
49.61
35.98
35.66
35.54
35.35 50.03
35.33 49.79
34.89 49.71
34.46 49.57
34.18 49.56
33.69 49.23
33.36 48.92
32.94 48.72
48.36
36.91
36.30
35.67
33.16 50.70
34. 18 50.26
33.32 49.80
32.47 49.43
31.70 48.72
30.97 48.09
30.55 47.48
30.43 46.92
46.39
35.22
34.04 51.19
32.85 50.33
31.67 49.47
30.48 48.61
29.30 47.75
28.12 46.89
26.93 46.03
25.75 45.17
24.56 44.31
23.38 43.45
42.59
NOTES: Projection I is computed based on NCES projections of degree recipients by major field of study.
Projection II is computed based on projecting the previous linear trend (1969 to 1978) in the female proportion
of degree recipients in each major field.
Projection III is computed based on projecting the previous linear trend (1969 to 1978) in the segregation index
for college majors.
SOURCES: Cols. (1) (except 1980), (3), (5), and (7) are computed from NCES (1980, pp. 66-71).
Col. (1), 1980; NCES (1981, pp. 19-24).
Col. (2), 1974 to 1981 is computed from Department of Labor, BLS, Employment and Earnings, 1974 (March),
1975 June), and 1976 through 1981 January).
Col. (2), 1972 is computed from BLS unpublished annual averages.
(1) a decline in the percentage of females in
nearly all traditionally female fields of study
(public affairs and services, library sciences,
letters, and education); and (2) an increase
in the representation of women in all other
fields. The largest upward trends are in the
traditionally male disciplines of architecture
(2.1 percent per year); agriculture and nat-
ural resources (2.5 percent per year); ac-
counting (2.4 percent per year); business and
management (2.0 percent per year); and
computer and information sciences (1.5 per-
cent per year). In each of these fields, be-
tween 1969 and 1978, the number of women
grew to around 25 percent of all majors;
according to our projections, they will be-
come 40 to 50 percent of these majors by
1989. The female proportion of psychology
majors also grew by 1.9 percent per year
during the 1970s. For such trends to con-
tinue the same conditions must prevail in
the future as in the recent past, even at the
higher number of female majors. That is,
women must not encounter substantial re-
OCR for page 104
104
ANDREA H. BELLER AND KEE-OK KID] HAN
Unlike the Census, the new Occupational
Employment Statistics (OES) survey con-
ducted by the BLS is a survey of jobs, not
of people. Projections based on such a ma-
trix avoid the problem of having to specify
an unemployment rate, but the primary dis-
advantage is the lack of consistency with CPS
data, which are based on a count of persons
rather than of jobs. The first set of these
new projections appears in Carey (19811.
As stated in the text of this paper, the
BLS occupational employment projections r
used assume that a stable Tong-run unem-
ployment rate close to 4.5 percent will be
achieved by the mid-1980s. This seems ex-
ceptionally optimistic from the vantage point
of the end of 1982 when, in September, the
economy hit a high unemployment rate of
10.1 percent. How would an unemployment
rate higher than 4.5 percent affect occupa-
tional employment projections for 1990? Ac-
cording to Carey (1981, p. 42), job growth
in blue-collar occupations is more sensitive
to the underlying assumptions than is job
growth in other major occupational cate-
gories. The need for additional blue-collar
workers is very much affected by the de-
mand for manufactured goods as well as by
changes in productivity. Job growth in the
white-collar and service categories generally
is less sensitive to the underlying assump-
tions than is blue-collar job growth. Most
likely the employment estimates would ov-
erestimate the size of blue-collar occupa-
tional employment. This consideration should
be kept in mind in examining the projec-
tions of occupational segregation, because
many blue-collar occupations are highly male,
and the larger they are the more they add
to the index of segregation.
The BLS 1990 occupational employment
projections "assume that the size, sex and
age composition of the labor force wiD change
as indicates] by the intermediate labor force
projections published by the BLS in Em-
ployment Projections of the 1980's." We use
those projections for our projections by age
cohort. Since the occupation projections are
based upon these labor force projections,
they should be consistent with them.
Methodology of Projections Based on Age
Cohorts
In order to make projections by age co-
hort, we need to know the sizes of age-sex
cohorts for the projected year to supplement
information on the projected occupational
distribution and the projected sex compo-
sition of each occupation. Age-sex-specific
projections on the size of the civilian labor
force in 1990, created by the BLS, are pre-
sented in Employment Projections for the
1980's. They project the size of age cohorts,
which we grouped into four categories: 16
to 24, 25 to 34, 35 to 44, and 45 + . Unfor-
tunately these categories cannot be trans-
formed into cohorts based on potential labor
market experience, which creates more
meaningful and presumably more homo-
geneous groupings for labor force analyses.
For example, the age group 16 to 24 contains
a mixture of high school graduates already
in their chosen field for several years and
individuals who are still students and who
work part time at jobs unrelated to their
future occupations. In the analyses by ex-
perience cohorts presented in another pa-
per, we excluded individuals with 0 years
of potential work experience (defined as
Age—Education—6), hoping to eliminate
students. Since we do not know the sizes of
age-sex experience cohorts for the projected
year, we must base our cohort projections
on age rather than on work experience co-
horts. Thus, we grouped our Annual De-
mographic File data for 1971 and 1977 into
age cohorts. Segregation indexes by age co-
hort for 1971 and 1977 shown in Table B-2
differ from those by experience cohort (Belier,
in this volume, Table 2-21. The youngest age
cohort is more segregated than is the young-
est experience cohort after exclusion of in-
OCR for page 105
OCCUPATIONAL SEX SEGREGATION: PROSPECTS FOR THE 1980s
105
dividuals with 0 years of potential experi-
ence.
To project what happened to a specific
cohort as it aged over time, we aged each
group backward to 1977 by subtracting 13
years. This yielded age groups in 1977 of 16
to 21, 22 to 31, and 32 to 41. We added the
age group 42 + to complete the labor force.
We also added the youngest complete co-
hort, 16 to 24 years of age, so that we could
use it for the projections as well. Aging the
groups backward! by 6 years to 1971 yielded
age groups 16 to 25, 26 to 35, and 36 to 45.
We added the group 46 + and the youngest
age cohort, 16 to 24. This construction can
be diagrammed as follows:
Group 1971 1977 1990
+6 +13
2
3
4
5
16-24 ~ 16-24 ~ 16-24
16-25 16-21 I
26-35 22-31 25-34
36~5 —`32-41 —`35-44
46+—42+ ~~45+
First, we must project the percentage of
males in each occupation for each age group
in 1990. To do this we choose three alter-
native assumptions, which allow for (1) no
change between 1977 and 1990; (2) changes
in the youngest cohort, group 1, only; and
(3) changes in all cohorts. Changes are pro-
jected to occur at the same rate between
1977 and 1990 as a given group ages as the
rate for the similar age group as it aged be-
tween 1971 and 1977. The methodology of
these three projections (labeled conserva-
tive, moderate, and optimistic) is described
in the text of this paper.
This method of projecting assumes that
the sex composition of occupations is char-
acteristic of the particular age cohort in
question rather than of the labor force or
the occupation. That is, it directs our atten-
tion to the characteristics of individuals, or
the supply side of the labor market, more
than do the projections based upon the whole
labor force, which direct our attention more
to the characteristics of employers, or the
demand side. Of course, supply changes in
response to perceived changes in demand.
Women's aspirations change as they per-
ceive reductions in the barriers to their en-
try into traditionally male occupations (Res-
kin and Hartmann, 1984~.
Once we create projections of the per-
centage of males in each occupation by age
group, we must combine them to create pro-
jections of the percentage of males in each
occupation for the labor force as a whole.
To obtain a labor force estimate from the
cohort estimates, we use the BLS projec-
tions on the age-sex distribution of the labor
force in 1990. We know the projected num-
ber of males, females, and total labor force
for each age group. We also know from BLS
projections the projected distribution of em-
ployment across occupations for the civilian
labor force as a whole. We need to combine
these two pieces of information to deter-
mine the occupational distribution of em-
ployment for each age group, and we must
make assumptions to do this. The simplest
assumption is that the occupational distri-
bution is the same for each age group as it
is for the labor force as a whole; this is equiv-
alent to standardizing the employment dis-
tribution of each subgroup to the employ-
ment distribution of the whole. (Thus, looking
ahead, when we use the projected sex com-
position within each occupation of each age
group to compute segregation indexes, we
will see differences in the indexes that are
bases] upon differences in their occupational
sex composition alone.) Another possible as-
sumption is that each age group has the same
occupational distribution of employment in
1990 as it did in 1977. This, too, is imper-
fect, because the occupational distribution
is projected to change. Consequently we
opted for the first approach.
We computed total employment, number
of males, and number of females in occu-
OCR for page 106
106
ANDREA H. BELLER AND KEE-OK KIM HAN
pation i in age group j in 1990 according to
the following:
Tij= zE x Tj, (A1)
My = Tij X pa,
~9 = Tij — My,
(A2)
(A3)
where Tij is total employment in occupation
i for age group j, where j = 1, . . . ,5 as in the
diagram above; Ei is total employment in
occupation i, given by BLS projections; T
. . . r
IS ClV1 1an a for force in age group 1, given
by BLS projections; pa is proportion male
in occupation i for age group j according to
cohort projection n, where n = 1,2,3; Mn'
is the number of males in occupation i for
age group j according to cohort projection
n; and Fill is the number of females in oc-
cupation i for age groupj according to cohort
projection n.
These numbers are then aggregated over
age groups to obtain the values for the ci-
vilian labor force in 1990:
Mn = ~ My,
i
Fn _ ~ Fn
i — ~ id,
pn = Mn + Fn
(A4)
(A5)
(A6)
Using these projections of proportion of males
by occupation and the BLS occupational
employment projections for 1990, Ei, we
compute four projected segregation indexes
for 1990, P5 to P8.
TABLE B-1 Actual and Projected Proportion Female for Detailed Occupations
Actual
Researchers and analysts, operas. and sys.
Personnel and labor relations
Pharmacists
Physicians, medics, and osteopaths
NEC, health technicians
Technicians, chemical
Draftsmen
Technicians, elect. engineers
Operators, radio
Public relations
Officers and manag., bank
NEC, managers, office
NEC, pub. admin., office and admin.
.2171
.1989
.0000
.0105
.0235
.0417
.0396
.0991
.3097
.1349
.1006
.5821
.1169
.0629
.0549
.3514
.2989
.1874
.4190
.2006
.3850
.2941
.0615
.0378
.1126
.1053
.1423
.2551
.4977
.2517
.1376
.5787
.2574
.1929
.1124
.5738
.4545
.3735
.7024
.2900
.0152 .4291
.0093 .3247
.0056 .1043
.0028 .0817
.0124 .1560
.0090 .1650
.0100 .1910
.0188 .2741
.0133 .5342
.0088 .3076
.0030 .1909
.0100 .6052
.0155 .3022
.0120 .2459
.0079 .1515
.0380 .5988
.0173 .5073
.0165 .4222
.0233 .7300
.0057 .3100
Occ.
Code Occupation Name
I. Proportion Female Increasing
1 Accountants
3 Programmers, computer
10 Engineers, chemical
12 Engineers, electrical and electronic
13 Engineers, industrial
25 Foresters and conservationists
31 Lawyers
55
56
64
65
85
151
152
153
171
192
202
220
222
1972 1981
Annual Projected
Rate 1.990
of
Change* (P1)
(P2) (p3)
.5239 .5476
.3822 .4113
.0964 .4129
.0594 .2666
.2442 .6959
.1879 .7742
.2284 .3644
.4188 .5883
.6028 .6063
.3240 .3563
.1620 .1681
.6721 .6666
.3965 .4874
.2884 .3763
.1882 .3061
.9790 .8860
.5721 .5847
.5204 .5530
.9356 .8628
.3414 .3496
NOTES: Column (P1) contains the linear-group projection, column (P2) contains the linear-individual projection,
and column (P3) contains the logistic-individual projection. NEC = not elsewhere classified.
*Coefficient estimate on linear time trend in individual occupation projection, where estimate is significant.
OCR for page 107
OCCUPATIONAL SEX SEGREGATION: PROSPECTS FOR THE 1980s _
107
TABLE B-1 (Continued)
occ.
Code Occupation Name
225
231
233
245
260
265
266
270
281
282
301 Bank tellers
305 Bookkeepers
315 Dispatchers and starters, vehicle
323 Expediters and production controllers
331 Mail carriers, post office
333 Messengers and office helpers
343 Computer and peripheral equip. operators
360 Clerks, payroll, and timekeep.
361 Postal clerks
375 Clerks, statistical
381 Storekeepers and stock clerks
390 Agents, ticket station and express
412 Bulldozer operators
415 Carpenters
422 Compositors and typesetters
430 Electricians
441 NEC, blue-collar supervisors
455 Locomotive engineers
470 Air coed., heating, refrigeration
481 Mechanics, heavy equipment
482 Mechanics and install. appliance home
550 Structural metal workers
552 Teleph. install and repairers
554 Teleph. linemen and splicers
601 Asbestos and insular. workers
631 Meat cutters, butchers, exe. manuf.
664 Shoemaking, machine operatives
666 Furnace tenders and stokers
703 Bus drivers
705 Delivery and route workers
715 Truck drivers
740 Animal caretakers, exe. farm
750 Carpenters' helpers
754 Garbage collectors
762
764
785
903
910
Actual
1972 1981
Annual Projected
Rate 1990
of
Change* (P1) (P2)
.3038 .0135
.4036 .0119
.1362 .0105
.1966 .0080
.4683 .0256
.2363 .0128
.2973 .0211
.5000 .0114
.2000 .0114
.1199 .0071
.9355 .0043
.9116 .0039
.3805 .0249
.4096 .0113
.1548 .0090
.2766 .0202
.6407 .0290
.8097 .0135
.3802 .0101
.8006 .0090
.3501 .0099
.4722 .0188
.0099 .0013
.0180 .0013
.3506 .0210
.0168 .0012
.1134 .0033
.0213 .0019
.0047 .0007
.0179 .0012
.0455 .0033
.0122 .0011
.0982 .0076
.0506 .0060
.0377 .0056
.0809 .0038
.7260 .0122
.0128 .0012
.4732 .0122
.0856 .0057
.0266 .0018
.5699 .0251
.0167 .0020
.0278 .0011
.2479 .0093
.1576 .0042
.1122 .0073
.1899 .0066
.4725 .0192
(P3)
.4648
.5422
.4391
.3049
.7241
.4173
.6537
.5934
.3553
.2506
.9586
.9399
.6883
.5159
.3091
.7250
.8555
.8965
.4919
.8667
.4689
.6732
.1623
.0610
.6181
.0496
.1562
.1108
.0434
.0472
.2108
.0488
.3495
.8681
.8507
.1402
.8248
.0527
.6071
.2172
.0686
.7822
.3307
.0385
.3530
.2017
.2881
.2759
.6688
NEC, purchasing agents and buyers
Retail trade sales manag. and dept. heads
Sales manag., exe. ret. trade
NEC, manag. and admin.
Adv. agents and sales work
Ins. agents, brokers, and underwriters
Vendors and carriers, news
Agents and brokers, real est.
Sales rep., manuf. indust.
Sales rep., wholesale trade
Stock handlers
Vehicle washers and equip. cleaners
Not specified laborers
Janitors and sextons
Bartenders
.1326
.2736
.0292
.1214
.2273
.1179
2444
.
.3668
.0700
.0460
.8715
.8794
.1628
.2308
.0667
.1410
.3776
.7174
.2669
.7090
.2290
.3178
.0000
.0049
.1647
.0043
.0701
.0000
.0000
.0070
.0152
.0000
.0194
.0000
.0000
.0348
.6184
.0123
.3414
.0247
.0042
.4125
.0160
.0118
.1687
.0909
.0396
.1051
.2786
.3426 .4148
.4732 .5299
.1944 .2242
.2424 .2724
.5063 .7100
.2867 .3508
.3193 .4734
.5440 .5916
.2596 .2870
.1681 .1837
.9501 .9749
.9327 .9517
.4065 .6186
.4561 .5056
.2026 .2444
.2934 .5129
.6596 .9335
.8367 .9446
.4025 .4824
.8364 .8913
.3958 .4550
.4941 .6625
.1239 .0232
.0831 .0303
.3803 .5491
.0720 .0255
.1606 .1434
.0784 .0334
.0628 .0125
.0936 .0285
.1178 .0673
.0787 .0191
.1378 .1684
.0771 .1072
.1000 .1037
.1307 .1135
.7223 .8539
.0507 .0201
.5038 .6043
.1420 .1393
.0923 .0401
.6387 .8100
.1150 .0351
.1731 .0347
.2911 .3267
.2149 .1920
.2181 .1778
.2407 .2503
.5156 .6604
(Continued)
OCR for page 108
108
ANDREA
_ BELLER AND KEE-OK KIM HAN
TABLE B-1 (Continued)
Actual Annual Projected
1972 1981 Rate 1990
Occ. of
Code Occupation Name Change* (P1) (P2) (P3)
-
932 Attendants, recreation and amuse. .3120 .4477 .0155 .4814 .6146 .6230
962 Guards .0461 .1366 .0086 .2062 .2017 .2936
II. Proportion Female Decreasing
141 Teach., adult ed.
142 Teach., elem. ed.
385 Telephone operators
502 Millwrights
624 Graders and sorters, manuf.
822 Farm laborers, wage workers
912 Cooks, exe. private household
915 Waiters
933 NEC, attendants, personal serv.
.3768 .4267 - .0219 .4759 .2106 .2364
.8505 .8359 - .0038 .8627 .8003 .7922
.9668 .9302 - .0040 .9469 .8984 .8480
.0000 .0000 - .0029 .0594 .0000 .0000
.7727 .6389 - .0162 .6869 .5119 .4772
.1535 .1594 - .0095 .1898 .0955 .1142
.6236 .5228 - .0109 .5616 .4344 .4318
.9173 .8967 - .0038 .9211 .8626 .8474
.6386 .5773 - .0117 .6077 .5135 .5096
III. Proportion Female No Significant Trend
2 Architects .0303 .0440 .0000 .1080 .0408 .0768
4 Syst. analysts, computer .1081 .2584 .0000 .2993 .3121 .3266
6 Engineers, aero- and astro-. .0000 .0122 .0000 .0467 .0124 .0245
11 Engineers, civil .0065 .0164 .0000 .0652 .0251 .0963
14 Engineers, mechanical .0000 .0243 .0000 .0652 .0396 .1713
23 N E C e n g i n e e r s .0000 .0290 .0000 .0544 .0335 .0524
32 Librarians .8278 .8580 .0000 .8745 .9020 .8914
44 S c i e n t i s t s , b i o 10 g i c a 1 .2778 .4035 .0000 .4609 .4525 .4563
45 Chemists .1008 .2090 .0000 .2577 .2866 .3452
75 Nurses, registered .9763 .9680 .0000 .9890 .9676 .9662
76 Therapists .5826 .7049 .0000 .7271 .7781 .7675
80 Clinical lab. techs. .7063 .7724 .0000 .7948 .7426 .7451
83 Radiologic techs. .6618 .6863 .0000 .7299 .5765 .5681
86 Clergy .0163 .0505 .0000 .0949 .0766 .0839
90 NEC, religious workers .5745 .4717 .0000 .5276 .4281 .4380
91 Economists .1176 .2484 .0000 .2927 .3620 .4014
93 Psychologists .3800 .4870 .0000 .5349 .4369 .4373
100 Social workers .5856 .6397 .0000 .6787 .5984 .5980
101 R e c r e a t i 0 n w 0 r k e r s .4457 .5798 .0000 .6288 .6511 .6487
140 Col. teach., not specified .2703 .3788 .0000 .8194 .4974 .4971
143 Teach., pre- and kindergart. .9681 .9833 .0000 1.0000 .9744 .9693
144 Teach., secondary sch. .4964 .5136 .0000 .5289 .4933 .4932
145 NEC, teach., exe. colt .7409 .7380 .0000 .7632 .7232 .7205
150 Technicians, ag. and biol., exe. health .2927 .4400 .0000 .4794 .5386 .5551
161 Surveyors .0141 .0114 .0000 .0563 .0188 .0743
162 NEC, techs., eng. and science .1437 .2469 .0000 .2970 .3083 .3218
163 Pilots, airplane .0000 .0125 .0000 .0769 .0152 .0278
174 Counselors, voca. and education .5000 .5323 .0000 .5648 .5559 .5558
180 Athletes and kindred .3077 .4351 .0000 .4610 .5434 .5495
183 Designers .1909 .2953 .0000 .3242 .4180 .4384
184 Editors and reporters .4110 .5050 .0000 .5465 .4908 .4901
185 Musicians and composers .3058 .2535 .0000 .3232 .1960 .2062
NOTES: Column (P1) contains the linear-group projection, column (P2) contains the linear-individual projection,
and column (P3) contains the logistic-individual projection. NEC = not elsewhere classified.
*Coefficient estimate on linear time trend in individual occupation projection, where estimate is significant.
OCR for page 109
OCCUPATIONAL SEX SEGREGATION: PROSPECTS FOR THE 1980s
109
TABLE B-1 (Continued)
Actual
Occ.
Code Occupation Name
190
191
194
195
201
205
210
212
215
216
223
224
230
235
240
262
264
271
283
284
285
303
310
312
313
314
320
321
325
326
330
332
341
345
355
364
370
372
374 Clerks, shipping and receiving
376 Stenographers
382 Teacher aides
391 Typists
392 Weighers
394 Misc. clerical workers
402 Bakers
404 Boilermakers
405 Bookbinders
410 Brick- and stonemasons
413 Cabinetmakers
1972 1981
Annual Projected
Rate 1990
of
Change* (P1)
.0000 .5424
.0000 .2868
.0000 .4272
.0000 .4107
.0000 .5311
.0000 .4735
.0000 .4042
.0000 .5442
.0000 .1545
.0000 .5572
.0000 .3034
.0000 .4121
.0000 .4356
.0000 .3506
.0000 .4010
.0000 .9663
.0000 .8295
.0000 .1915
.0000 .7504
.0000 .2502
.0000 .5146
.0000 .9286
.0000 .8960
.0000 .7469
.0000 .6740
.0000 .8051
.0000 .7842
.0000 .5754
.0000 .8619
.0000 .6189
.0000 .8600
.0000 .5136
.0000 .9329
.0000 .9494
.0000 .7156
.0000 .9961
.0000 1.0000
.0000 1.0000
.0000 .2734
.0000 .8790
.0000 .9634
.0000 .9891
.0000 .3996
.0000 .8716
..
.0000 .4427
.0000 .0840
.0000 .6064
.0000 .0842
.0000 .0904
(P2) (P3)
.5559 .5558
.1829 .1776
.3115 .3171
.4774 .4896
.6337 .6356
.5175 .5198
.4803 .4986
.4941 .4937
.2487 .3676
.5134 .5134
.3114 .3140
.5071 .5347
.3893 .3893
.3923 .4001
.4255 .4313
.9726 .9720
.9441 .9106
.2186 .2461
.7298 .7302
.2032 .2040
.4648 .4654
.9654 .9362
.8715 .8715
.7731 .7631
.7942 .7702
.7804 .7831
.5988 .4914
.5879 .5875
.8068 .8027
.7291 .7181
.9261 .9012
.4977 .4978
.8085 .7311
.9866 .9701
.5438 .4820
.9792 .9770
.9851 .9733
.9921 .9922
.2667 .2769
.8164 .7413
.9680 .9536
.9745 .9728
.2969 .3035
.8911 .8778
·4737 .4762
.0000 ~0010
.5671 .5783
.0000 .~Q2
.0279 .0258
Painters and sculptors
Photographers
NEC, writers, artists, entertainers
Research, not specified
Assessors, controllers, treasurers
Buyer, whole. and retail
Manager, credit and collect
Administrators, health
Inspectors, exe. construct., pub. admin.
Manag. and superintendent, building admin.
Officials, lodges, sac. and unions
Mail super. and postmasters
Manager, rest., bar, cafeteria
Sch. admin., college
Sch. admin., sec. and elem.
Demonstrators
Hucksters and peddlers
Sales agent, stock and bond
Sales clerks, retail trade
Sales work, exe. clerks, retail
Sales work, service and construe.
Billing clerks
Cashiers
NEC, supervisors, clerical
Collectors, bill and account
Clerks, counter, exe. food
Enumerators and interviewers
NEC investigator and estimator
File clerks
Insur. adjusters, examiners, and investigators
Library attend. and assist.
Mail handlers, exe. post office
Bookkeep. and billing operators
Key punch operators
NEC, office machine operators
Receptionists
Secretaries, legal
NEC, secretaries
in. . ,
.4264 .5121
.1558 .2424
.3333 .3853
.2791 .3936
.3448 .5000
.3292 .4346
.2535 .3788
.4746 .4954
.0619 .1019
.4265 .5063
.1875 .284s
.3409 .3636
.3239 .404s
.2530 .35O4
.26a4 .3668
.9375 .9619
.7304 .7964
.osso .1667
.6887 .7130
.1302 .1965
.2941 .4304
.8456 .8808
.8667 .8637
.s779 .7073
.4833 .6444
.7386 .7642
.820s .7544
.4339 .5444
.8493 .8371
.3519 .5753
.7518 .82sS
.4375 .4767
.9130 .8936
.897s .9383
.6949 .6833
.9702 .9742
.9908 .9888
.9909 .9914
.1486 .2272
.9040 .8611
.8932 .9303
.9608 .9634
.2791 .3421
.7513 .8200
.289s .4148
.0000 .oooo
.62s0 .5600
.ooss .oooo
.oSoo .0267
(Continued)
OCR for page 110
110
ANDREA H. BELLER AND KEE-OK KIM HAN
TABLE B-1 (Continued)
Actual
Occ.
Code Occupation Name
652 Lathe and mill machine operatives .0488
653 NEC, precision machine operatives .1475
656 Punch and stamp press operatives .2739
662 Sawyers .0496
421 Cement and concrete finishers .0127
424 Crane, derrick, hoist operators .0467
425 Decorators and window dressers .5977
433 Install. and repair elect. power lines .0098
436 Excavat., grading, exe. bulldozer .0000
452 NEC, inspectors .0305
454 Job and die setters, metal .0106
461 Machinists .0054
471 Aircraft .0000
472 Auto body repairers .0000
473 Auto mechanics .0058
475 Repairers, data process. machine .0222
480 Farm implement .0000
484 Office machine .0000
485 Radio and television .0081
503 Molders, metal .0962
510 Painters, construct. and maintenance .0188
522 Plumbers and pipe fitters .0027
530 Printing press operator .0563
534 Roofers and slaters .0000
535 Sheetmetal workers and tinsmiths .0139
545 Stationary engineers .0105
551 Tailors .3226
561 Tool and die makers .0058
563 Upholsterers .1364
575 NEC, craft and kindred workers .0690
602 Assemblers .4671
604 Bottling and can operatives .3455
610 Checkers, examiners, inspect manuf. .4847
611 Clothing-ironers and pressers .7683
612 NEC, cutting operatives .2773
615 Drywall install. and lathers .0120
621 Filers, sanders, polishers, buffers .2213
622 Furnace tenders, smelters, pourers .0429
623 Garage work and gas stat attend. .0458
625 Produce graders and packers, exe. fact. and farm .7143
630 NEC, laundry and dry clean. opera. .6970
633 Meat cutters, butchers-manuf. .3258
634 Meat wrappers, retail trade .9000
640 NEC, mine operatives .0070
641 Mixing operatives .0202
642 Oilers and greasers, exe. auto .0435
643 Packers and wrappers, exe. meat and produce .6090
1972 1981
Annual Projected
Rate 1990
of
Change* (P1) (P2) (P3)
.0594 .0000
.1754 .0000
.3208 .0000
.0909 .0000
.0000 .0000
.0070 .0000
.7222 .0000
.0086 .0000
.0062 .0000
.0839 .0000
.0532 .0000
.0388 .0000
.0325 .0000
.0098 .0000
.0058 .0000
.0700 .0000
.0000 .0000
.0400 .0000
.0367 .0000
.1731 .0000
.0575 .0000
.0044 .0000
.1091 .0000
.0000 .0000
.0397 .0000
.0165 .0000
.4091 .0000
.0237 .0000
.2222 .0000
.1746 .0000
.5231 .0000
.4231 .0000
.5356 .0000
.8067 .0000
.3137 .0000
.0127 .0000
.3186 .0000
.0323 .0000
.0559 .0000
.7333 .0000
.6614 .0000
.2917 .0000
.8980 .0000
.0192 .0000
.0390 .0000
.0526 .0000
.6339 .0000
.1331 .0568
.2521 .0835
.4124 ·3544
.1591 .1553
.1030 .0000
.0941 .0124
.7627 .8934
.0618 .0044
.0740 .0113
.1364 .1619
.1211 .0661
.0861 .0769
.0916 .0414
.0675 .0217
.0685 .0068
.1298 .0930
.0995 .0004
.1086 .0481
.1216 .0406
.2276 .1990
.1149 .1114
.0595 .0092
.1595 .1350
.0477 .0000
.1069 .0577
.0639 .0316
.5666 .5151
.0878 .0276
.2612 .1425
.2648 .4046
.5787 .5462
.4710 .4176
.5743 .5239
.8334 .7846
.3606 .3047
.1034 .0272
.3614 .2806
.1058 .0965
.1048 .0797
.7699 .8337
.7044 .6600
.3297 .2832
.9357 .8358
.0610 .0336
.0998 .0287
.1189 .0719
.6827 .6354
.0583
.0994
.3556
.6861
.0010
.0068
.8542
.0053
.0315
.2269
.0283
.2243
.0486
.1132
.0066
.2669
.0011
.0456
.0501
.2099
.2060
.0124
.1699
.0006
.0911
.1634
.5344
.0337
.1499
.6389
.5461
.4183
.5240
.7831
.3049
.0790
.2813
.7333
.1100
.8241
.6594
.2832
.7171
. 1333
.0330
.2183
.6352
NOTES: Column (P1) contains the linear-group projection, column (P2) contains the linear-individual projection,
and column (P3) contains the logistic-individual projection. NEC = not elsewhere classified.
*Coefficient estimate on linear time trend in individual occupation projection, where estimate is significant.
OCR for page 111
OCCUPATIONAL SEX SEGREGATION: PROSPECTS FOR THE 1980s
111
TABLE B-1 (Continued)
ocC.
Code Occupation Name
l-
644
645
650
651
663
665
672
674
680
681
690
692
694
695
706
711
712
713
714
751
753
755
760
761
770
82
901
902
911
913
914
916
921
922
925 Nursing aides, orderlies, attend.
926 Practical nurses
942 Child care workers, exe. private
944 Hairdressers and cosmetologists
950 Housekeepers, exe. private house.
952 School monitors
954 Welfare service aides
960 Crossing guards and bridge attend.
961 Firemen, fire protection
964 Police and detectives
965 Sheriffs and bailiffs
980 Child care workers, priv. house.
984 Private house cleaners and servants
Actual
1972 198
Annual Projected
Rate 1990
of
Change* (P1)
.1667 .0000
.5177 .oooo
.2500 .oooo
.1119 .oooo
.9603 .oooo
.7292 .0000
.673s .oooo
.5s20 .0000
.0465 .0000
.4546 .0000
.2913 .0000
.2781 .0000
.3526 .oooo
.3452 .0000
.0579 .oooo
.1000 .0000
.oooo .oooo
.oooo .oooo
.0932 .oooo
.0215 .0000
.0966 .0000
.0463 .0000
.0227 .oooo
.0101 .0000
.0595 .oooo
.0645 .0000
.9657 .0000
.5534 .oooo
.1982 .oooo
.2892 .0000
.8370 .oooo
.7342 .0000
.9784 .oooo
.8454 .oooo
.8665 .0000
.9772 .oooo
.9544 .oooo
.8936 .oooo
.6992 .oooo
.9722 .0000
.8837 .oooo
.6222 .oooo
.0095 .oooo
.0557 .oooo
.0725 .oooo
.9774 .oooo
.9519 .oooo
(P2) (P3)
.1469 .1458
.sso3 .5501
.2607 .2618
.2038 .2699
.9558 .9565
.6354 .6065
.6720 .6727
.5060 .5056
.0526 .0530
.5856 .5873
.2769 .2773
.3625 .3640
.3553 .3553
.4835 .4974
.0909 .2624
.1283 .5642
.0163 .0088
.0175 .0092
.0902 .0936
.0454 .0875
.1106 .1139
.0917 .1719
.0299 .0654
.0000 .0015
.0723 .0783
.1937 .2039
.9454 .9174
.5830 .5826
.2882 .3110
.3540 .3527
.8788 .8709
.7387 .7391
.9761 .9840
.9321 .9084
.8682 .8698
.9652 .9131
.9084 .8760
.8647 .8490
.6274 .6095
.0000 .9328
.9086 .9035
.5411 .5378
.0057 .0065
.0856 .0987
.1099 .3588
.9690 .9721
.9395 .9320
Painters, manufactured articles
Photographic process workers
Drill press operatives
Grinding machine operatives
Sewers and stitchers
Solderers
Spinners, twisters, and winders
NEC, textile operatives
Welders and flame-cutters
NEC, winding operatives
Machine operatives, misc. specified
Machine operatives, not specified
Misc. operatives
Not specified operatives
Fork lift and tow motor operatives
Parking attendants
RR brake operators and couplers
RR switch operators
~ . . . . . , ~
.146
.4691
.2267
.0538
.9583
.7674
.6071
.5282
.0361
.4658
.2814
.2148
.3166
.3036
.ooss
.0303
.oooo
.oooo
taxicab drivers and cnauneurs .0904
Construction laborers, exe. carpenters' helpers .0049
Freight and material handlers .0604
Gardeners and groundskeepers, exe. farm .0221
Longshore workers and stevedores .0000
Timber cutting and logging .0123
NEC, warehouse laborers .0267
Farm supervisors .0357
Cleaners, lodging quarters- exc. .9786
NEC, building interior cleaners .5509
Waiters' assistants .1367
Dishwashers .3578
Food counter and fountain workers .8208
NEC. food service workers, exe. private house. .7377
.9787
.7973
.8344
.9650
.9579
.9089
.7094
.8750
.8235
.6327
.0050
.0264
.0508
.9797
.9719
Dental assistants
Health aides, exe. nursing
.2314
.5679
.2936
.1499
.9908
.7299
.7174
.ss59
.1125
.5402
.3408
.3387
.3643
.4101
.1220
.1922
.0525
.0553
.1361
.0905
.1544
.1002
.0857
.0302
.0715
.1211
.0000
.5992
.2802
.3645
.8752
.7723
.0000
.8932
.9034
.0000
.9839
.9171
.7424
.9962
.9173
.6625
.0775
.1125
.1230
.9853
.9700
OCR for page 112
112
ANDREA H. BELLER AND KEE-OK KIM HAN
TABLE B-2 Actual and Projected Segregation Indexes by Age Cohort, 1971 to 1990
1971 1977 Projected 1990
Group Age U ES Age U ES Age (P5) (P6) (P7) (P8)
1 16-24 68.64 67.14 16-24 64.68 61.86 16-24 61.96 37.08 46.60 37.08
2 16-25 68.31 67.33 16-21 65.49 66.04 -
3 26-35 68.94 68.90 22-31 62.67 61.81 25-34 66.18 66.18 47.82 39.61
4 36-45 70.85 70.77 32-41 66.30 67.48 35-44 61.91 61.91 55.02 49.63
5 46+ 68.62 69.16 42+ 66.86 67.61 45+ 68.19 68.19 58.17 48.90
Total 68.14 64.15 - 62.11 57.29 50.02 42.20
NOTES: The age groups are constructed so that each group can be followed as it ages over time. Thus, the
difference between the 1971 and 1977 intervals is 6 years and between the 1977 and 1990 intervals, 13 years.
U = unstandardized, and ES = standardized to the employment of the whole labor force in the given year.
SOURCES: 1971 and 1977: Current Population Survey, Annual Demographic Files, 1972 and 1978, computer
tapes; 1990: Department of Labor, BLS (1979, Table 4, p. 5~; Department of Labor, BLS (1981, Table 5, pp. 495-
502~.
TABLE B-3 Actual and Projected Proportion Female for College Majors, 1969 to 1989
Actual Projected
Percent Female Percent
1969 1978 Trenda Female, 1989
Field of Study (1) (2) (by (4)
Social sciences 36.3 41.0 0.005 45.5
Psychology 42.9 58.8 0.019 79.4
Public affairs and services 71.6 49.4 -0.026 10.8
Library sciences 93.6 88.5 - 0.003 87.4
Architecture and environment design 4.3 23.7 0.021 47.0
Fine and applied arts 59.1 62.0 0.004 66.4
Foreign languages 73.1 75.9 0.003 79.7
Communications 42.2 46.9 0.007 51.0
Letters 63.4 57.1 - 0.008 46.9
Mathematics and statistics 37.4 41.1 0.005 47.5
Computer and information sciences 13.0 25.7 0.015 40.7
Engineering 0.7 7.4 0.006 11.5
Engineering technologies 0.5 2.8 0.003 6.4
Physical sciences 13.6 21.3 0.009 30.4
Biologic sciences 28.0 38.4 0.012 50.6
Agriculture and natural resources 3.8 24.6 0.025 50.1
Health care professions 76.9 80.5 0.004 84.0
Accounting 7.8 29.4 0.024 52.7
Business and management 9.1 26.4 0.020 45.4
Education 75.8 72.5 - 0.004 67.2
Other 53.1 58.4 0.007 66.1
All fields 43.7 47.1 52.3b
a The trend value is the estimated coefficient on year in an OLS regression equation in which the percentage
of females is regressed on time. All trend values are significant at the .05 level except communications, which is
significant at .10 level.
b Computed from the projected sex composition for each major field.
SOURCE: NCES (1980, pp. 70-71~.
OCR for page 113
OCCUPATIONAL SEX SEGREGATION: PROSPECTS FOR THE 1980s
113
APPENDIX C PROJECTIONS FOR
PROFESSIONAL OCCUPATIONS BASED
UPON COLLEGE MAjORS
The mode! used to project segregation
among professional occupations based on
segregation among college majors departs
from the other models used in this paper.
In this mode! the segregation index itself,
rather than the sex composition of each oc-
cupation, becomes the data point. We chose
this model because attempts to relate the
sex composition of a professional occupation
to that of a specific college major proved
unsuccessful. Thus, we hypothesized that
the overall degree of segregation among col-
lege graduates would affect the overall de-
gree of segregation in professional occupa-
tions.
The data used for these projections for
professional occupations are slightly di~er-
ent from the data used earlier in this paper.
To obtain a continuous time series, data were
taken from the published BLS AA data (Em-
ployment and Earnings, various issues). The
female proportion of occupational employ-
ment was first published in 1974. Initially
each published category represented an in-
dividual occupation or a combination of oc-
cupations having a minimum employment
estimate of 150,000; the sex distribution was
included only where the basis of the esti-
mate was at least 15,000. By this criterion
the sex distribution was not published for
many detailed categories. Consequently to
obtain comparable data over time, more ag-
gregate categories of professional occupa-
tions were used in these analyses. Twenty-
four separate categories were used for 1978
to 1981, 23 for 1975 to 1977, ant! 18 for 1974.
We also used unpublished AA data for 1972
and used the same 24 categories as in 1978
to 1981. Thus, the segregation indexes used
here differ slightly from the other ones re-
ported in this paper, which include 59 dis-
aggregated categories. For example, the
segregation index for professional occupa-
tions based on the published aggregated data
is 49.61 in 1981, while that based on un-
published detailed data is 50.55. As is com-
mon, the aggregation tends to mask some
segregation, but the effect here is small. It
is even smaller in 1977, when the segre-
gation index based on 23 aggregated cate-
gories is 54.07 and based on 59 detailed oc-
cupations is 54.35. The index baser! on
unpublished aggregated data in 1972 is 58.94,
while that based on detailed data is 59.44.
Thus, the elect of this aggregation appears
to be to somewhat overstate the decline in
segregation in professional occupations dur-
ing the 1970s.
ACKNOWLEDGMENTS
Discussions with Francine Blau, John
Boyd, and Kenneth Stolarsky stimulated the
development of ideas. Helpfi~l comments on
an earlier draR were provided by Marianne
Ferber, Barbara Reskin, and several re-
viewers. Computational assistance by John
Boyd and Alex Kwok is gratefully acknowI-
edged.
REFERENCES
Becker, Gary S.
1971 The Economics of Discrimination. Chicago:
University of Chicago Press.
Beller, Andrea H.
1982a "The Impact of Equal Opportunity Policy on
Sex Differentials in Earnings and Occupa-
tions." American Economic Review, Papers and
Proceedings (May):171-75.
1982b "Occupational Segregation by Sex: Determi-
nants and Changes." Journal of Human Re-
sources 17 (Summer):371-92.
Blau, Francine D., and Wallace E. Hendricks
1979 "Occupational Segregation by Sex: Trends and
Prospects." Journal of Human Resources 14
(Spring): 197-210.
Carey, Max L.
1981 "Occupational Employment Growth Through
1990." Monthly Labor Review 104~8~:42-55.
Department of Labor, Bureau of Labor Statistics
1979 Employment Projections for the 1980's. Bul-
letin 2030. Washington, D.C.: U.S. Govern-
ment Printing Office. June.
1981 The National Industry-Occupation Employ-
ment Matrix, 1970, 1978 and Projected 1990.
Bulletin 2086, Vol. 2. Washington, D.C.: U.S.
OCR for page 114
114
Government Printing Office. April. Employ-
ment and Earnings. Various issues.
Lloyd, Cynthia, and Beth Niemi
1979 The Economics of Sex Differentials. New York:
Columbia University Press.
Medoff, James L.
1979 "Layoffs and Alternatives Under Trade Unions
in U. S. Manufacturing." American Economic
Revieu; 69 June):380-95.
National Center for Education Statistics
1980 Projections of Education Statistics to 1988-89.
By Martin M. Frankel and Debra E. Gerald.
April.
1981 Earned Degrees Conferred 1979-80. Septem-
ber.
Osterman, Paul
1982 "Affirmative Action and Opportunity: A Study
ANDREA H. BELLER AND KEE-OK KIM HAN
. .
Of Female Quit Rates." Review of Economics
and Statistics 64~4~:604-12.
Poirier, Dale J.
1976 The Econometrics of Structural Change, With
Special Emphasis on Spline Functions. Am-
sterdam: North-Holland.
Reskin, Barbara F., and Heidi I. Hartmann
1984 Women's Work, Men's Work: Sex Segregation
on the Job. Washington, D.C.: National Acad-
emy Press.
Smith, Ralph E.
1977 "1he Impact of Macroeconomic Conditions on
Employment Opportunities for Women." Pa-
per No. 6, prepared for U.S. Congress, Joint
Economic Committee, 94th Cong., 2d sess.
Representative terms from entire chapter:
professional occupations
