The female-male unemployment differential: effects of changes in industry employment Essay

Over time, a significant change in the relationship between male and
female unemployment rates has occurred. Between 1970 and 1981, the
female unemployment rate averaged 1.5 percentage points higher than the
male rate. However, in 1982, the male unemployment rate (9.9 percent)
exceeded the female rate (9.4 percent) for the first time since such
data were recorded beginning in 1947. This reversal in unemployment
rates is the apparent culmination of a narrowing of the differential
that began in 1978. (Shee chart 1.)



Although male unemployment rates generally increase more than
female rates during recessions (see the shaded areas in chart 1), the
relative worsening experienced by men during the 1981-82 recession was
greater than in previous downturns. (And, as noted, the female-male
unemployment rate differential began to narrow prior to the recession,
which is inconsistent with historical patterns.) Are we witnessing a
long-term improvement in the unemployment situation of women relative to
men? To what extent are the observed changes due to trends in
interindustry growth rates in employment which may favor one sex over
the other? This article addresses these questions using a modified version of shift-share analysis (see appendix A) to estimate the effect
that change in employment patterns among industries has had on the
female-male unemployment rate differential since 1964, and to project
likely future effects through 1995. Shirt-share analysis is commonly
used to disagregate regional employment change in an industry in order
to identify the components of that change. The applciation of
shift-share analysis in this article, however, is to disaggregate annual
changes in the male-female unemployment differential into three
components.


Many researchers have observed the procyclical nature of the
female-male unemployment rate differential. Because men tend to be
concentrated in those industries which are most sensitive to the
business cycle (particularly manufacturing, construction, and mining),
it is not surprising that male unemployment rates rise relative to
female rates during recessions and fall during recoveries. But
industries also change their employment requirements in response to
forces other than the business cycle. For example, in recent years,
automobile and steel manufacturing employment has experienced a secular decline because of increased foreign competition and laborsaving technological changes. Such longer term trends have an impact on
unemployment differentials between men and women.



The effect that the growth (or decline) of a given industry has on
the female-male unemployment rate differential depends on several
factors, inclunding:



* The rate of growth (or decline) of the industry.



* the percentage of total employment in the industry which is
female (or male);



* the interindustry mobility of men and women in response to
changes in employment opportunities in the industry; and



* the labor force mobility of men and women in response to changes
in employment opportunities in the industry.



Information on the first two factors is presented in table 1. It
shows the average annual rate of growth of employment in nine broadly
defined industries during 1964-82. Clearly, employment grew most
rapidly in those industries which employ the highest proportion of
women, particularly services, and finance, insurance, and real estate.
This trend in industry growth rates has contributed to the narrowing of
the female-male unemployment rate differential. However, it is important
to note that the mobility of men and women between industries and into
and out of the labor force must be “less than perfect” for
changes in the industrial composition of employment to have an effect on
the unemployment differential. Otherwise, an increase in unemployment in
an industry would quickly be offset by the movement of unemployed
workers to other industries (interindustry mobility) or by an exit of
unemployed workers from the labor force (labor force mobility).
Industry growth differentials would then have no direct effect on male
and female unemployment rates. With perfect mobility, men who lose
their manufacturing jobs would quickly join the growing service
industries or drop out of the labor force. Research has shown, however,
that unemployed men and women do not exhibit perfect interindustry and
labor force mobility.


in sum, it appears that the four factors previously cited would
tend to decrease the female-male unemployment rate differential. First,
female-dominated service-producing employment is growing faster than
male-dominated goods-producing employment. Second, because
interindustry and labor force mobility is less than perfect, variations
in employment demand will influence unemployment rates. The trend
towards slower goods-producing growth rates relative to services
implies, then, that the recent reversal in the female-male unemployment
rate differential could be the result of secular growth differentials
among industries as well as the severe recession.



The following section presents a shift-share technique which is
used to measure the effects of relative changes in industry employment
on the female-male unemployment rate differential from 1964 to 1982. In
a subsequent section, this technique is applied to BLS employment
projections to predict how expected future trends in industry employment
growth would affect female-male unemployment rate differentials. The
appendices develop the methodology in greater detail. Components of
change in differentials



Shift-share analysis has frequently been used to analyze the source
of regional employment growth, but seldom to disaggregate the components
of change in unemployment differentials. (See table 2.) The purpose of
the shift-share analysis is to dissect the year-to-year change in the
female-male differential into three components: national share effect,
industry mix effect, and employment shift effect. The sum of these
effects equals the total change in the unemployment differential. The
analysis starts with very restrictive assumption regarding labor force
and interindustry employments trends and proceeds to relax these
assumptions one at a time.



National share effect. This effect is computer by assuming that
male and female employment in each industry changes at the same rate as
total national employment. The male and female labor forces are each
assumed to grow at the same rate as the total labor force. The national
share effect shows how the female-male unemployment rate differential
would have changed from year to year if: (1) the proportion of men and
women in each industry remained unchanged, (2) the proportion of men and
women in the labor force remained unchanged, (3) the share of each
industry’s employment in total employment was constant, and (4)
total employment and the labor force grew at their actual rates.



Under these assumptions, male and female employment and labor
forces change at the same rate. Because the unemployment rate is
defined as: 1 – number employed/, number in labor force this results in
proportionate changes in male and female unemployment rates. The
national share effect on the female-male differential is thus
procyclical but trivial in magnitude.



Industry mix effect. To calculate the industry mix effect, the
assumption that each industry grows at the national rate is dropped.
Employment in each industry is postulated to grow at its actual rate,
but it is assumed that the proportion of men and women employed in each
industry remains the same as in the previous period. If employment in
female-male-dominated industries, as appears indicated in table 1, the
industry mix effect will reduce the unemployment rate of women relative
to that of men.



When employment increases in an industry, the additional workers
will be drawn into employment from the ranks of the unemployed and from
outside the labor force. Therefore, an assumption is needed about how
this effect changes the labor force. It is assumed that men and women
who “enter” employment as a result of the industry mix effect
come from the unemployment pool and from outside the labor force in the
same proportions as they actually did during the previous year.
Similarly, when the industry mix effect causes a decrease in employment,
it is assumed that men and women who exit employment leave the labor
force or become unemployed in the same proportions as they actually did
during the previous year. (This procedure is discussed in detail in
appendix A.) It is also assumed, in the computation of the
interindustry effect, that there is no net interindustry mobility of
labor.



The industry mix effect shows how differing industry growth rates
affect the female-male unemployment rate differential when there are
different percentages of men and women in each industry. (See table 2.)
When the effect is negative, female-dominated industries are growing
faster (or declining less) than male-dominated industries, reducing the
female-male unemployment rate differential. When the effect is
positive, male-dominated industries are growing faster (or declining
less) than female-dominated industries, thereby increasing the
differential.



The industry mix effect appears to have both a cyclical component
and a secular trend. The cyclical component is suggested by the
industry mix effect always being negative during recession (for example,
1970-71, 1974-75, and 1981-82) and positive only during expansions.
This is because employment is more cyclically variable in male-dominated
industries than in those which are female-dominated. For example, the
three industries that are most sensitive to the business cycle (mining,
construction, and manufacturing) are very much male-dominated. (See
table 1.)



The industry mix effect shows smaller positive changes in each
successive expansion and generally larger negative changes in each
successive recession, which suggests that there may be a long-term trend
which lowers female unemployment rates relative to male rates. (See
table 2.) To determine whether there is a significant trend in the
industry mix effect which is independent of the business cycle, a
regression equation was estimated for the 1964-82 period which predicts
the impact of the business cycle (as measured by the help-wanted
advertising index) and trend variables on changes in the industry mix
effect over time. The regression results presented in appendix B, show
that the trend and the business cycle were both highly significant
predictors of change. After controlling for cyclical effects, the
female-male differential declined on average by about 0.2 percentage
points per year. These results indicate that the differential
employment growth rates of industries have tended to favor
female-dominated industries and that this has caused a narrowing in the
female-male unemployment rate differential, even after accounting for
the short-term effects of the business cycle.



Employment shift effect. This effect is the change in the
male-female unemployment differential that remains after accounting for
the national share and industry mix effects. Two factors determine the
sign and the magnitude of this effect. The first is the difference in
the rates of growth in the male and female labor force. The fact that
the female labor force has been expanding more rapidly than the male
labor force tends to cause unemployment rates of women to be greater
than those of men. The second factor which determines the employment
shift effect is the change in the male-female employment composition
within industries. If an industry increases the proportion of women it
employs, the unemployment rate of women will decrease relative to that
of men. The following tabulation presents the proportion of women
employed in each industry during 1964 and 1982 and the average annual
percentage change in that proportion. These data show significant
differences among industries in the rates at which the proportions of
female employment have increased.



The employment shift effect can be thought of as representing the
ability of industries to respond to changes in labor force participation
rates of men and women by altering the distribution of their employment
between sexes. Perfect accommodation to changes in labor force
participation would result in an employment shift effect which equals
zero. However, if the share of female employment within industries does
not rise by enough to accommodate the increase in female labor force
participation, the employment shift effect would be positive. This
would tend to increase female unemployment rates relative to the male
rate. And finally, where the share of female employment in the industry
advances by more than enough to accommodate the increase in female labor
force participation, the employment shift effect would be negative.
This would tend to decrease the female unemployment rate relative to the
male rate.



We note that the employment shift does not exhibit the same kind of
cyclical behavior as the industry mix effect. For example, during the
1970-71 and 1974-75 recessions, the employment shift effect favored men,
but during the 1980 and 1981-82 recessionary period it favored women.
(See table 2.) This is a potentially important development because it
may represent a change in the ability and willingness of individual
industries to absorb women into employment. Regression results show,
however, that on average, during the 1964-82 period, the employment
shift effect shows no significant trend or cyclical response. (See
appendix B.)



In recent years (1979-82), all three effects–the national share
effect, industry mix effect, and employment shift effect-contributed to
reducing the female-male unemployment rate diffeential. The industry
mix effect indicates that, as in previous recessions, the 1980 and
1981-82 downturns affected male-dominated industries more severely than
female-dominated ones. But there is also a trend in the industry mix
effect independent of the business cycle. This means that long-term
industry-specific employment trends have favored women’s employment
because of their greater concentration in those industries with the
highest long-term growth rates. Finally, an examination of the
employment shift effect shows that since 1979 many industries more
readily employed women entering the work force, but that there has been
no such long-term trend. Employment projections



Will employment trends continue to improve the unemployment
situation of women relative to men? The preceding analysis suggests
that this will depend to a large extent on the future growth rates of
female- versus male-dominated industries. The Bureau of Labor
Statistics projections of employment by industry make it possible to
analyze the probably impact of the industry mix effect on the future of
the female-male unemployment diffeential. Table 3 presents the average
annual rates of change in projected employment between 1982 and 1990 and
between 1990 and 1995. The BLS made three sets of projections for each
time frame: the first assumes low rates of economic growth; the second,
moderate growth rates; and the third, high growth rates. Valerie A.
Personick describes the moderate growth scenario as follows:



Table 3 shows significant differences in projected employment
growth rates among industries under each of the three growth scenarios.
It also indicates that, expect for the construction industry, women are
currently overrepresented in the high-growth-rate industries (for
example, services and finance, insurance, and real estate). Women
represent only 25.5 percent of total employment in the five industries
which are projected in the moderate scenario to grow by 13.2 percent
between 1982 and 1990. However, women constitute 51.6 percent of
employment in the four service-oriented industries projected to increase
by 18.9 percent. It appears that future trends in employment will
continue to favor a reduction of the unemployment rates of women
relative to men’s.



What are the implications of these trends for the female-male
unemployment rate differential? The following tabulation presents the
results of a partial shift-share analysis of changes in female-male
unemployment rate differentials which would occur between 1982 and 1990
and between 1982 and 1995 under each of the three economic growth
scenarios:



Because BLS does not project male and female employment by
industry, it is possible to calculate only the industry mix effect. Its
computation assumes that employment in each industry grows at its
projected rate and that the proportions of men and women in each
industry remain at the 1982 levels. Also, male and female labor force
entry and exit patterns are assumed identical to those of 1982. Under
these assumptions, the female unemployment rate would decrease by about
2 percentage points relative to the male rate between 1982 and 1990 and
would decrease by approximately 2.4 percentage points between 1982 and
1995. The industry mix effect would continue its 1964-82 trend,
exerting downward pressure on the female-male unemployment rate
differential by about 0.2 percentage points per year.



It should be noted that the impact of the changing industry mix on
the differential is likely to be modified by seveal factors which are
not measured in the partial shift-share analysis. First, the BLS
projections of employment growth between 1982 and 1995 do not allow for
cyclical variation, apart from the current recovery. The results for
1964-82 imply that the industry mix effect is strongly affected by the
business cycle, and thus the results reported in the tabulation
represent only the trend component of this effect. There will
undoubtedly be substantial year-to-year cyclical variation in the
female-male unemployment differential during 1982-95. Second, male
interindustry mobility may increase over past rates as the relatives
secular decline in goods-producing industries continues. Men may
increase their employment share in the rapidly growing industries,
decreasing their projected unemployment rate. Third, female labor force
participation rates will continue to rise during the next decade, and
women’s attachment to the labor force has also been increasing.
These factors would tend to boost female unemployment rates over their
industry mix levels. Both of these trends–the possible rise in the
male share of rapidly growing industries, and the continuing increase in
the female participation rate–would be reflected in a positive
employment shift effect over the 1982-95 period.



Still, the projected relative secular decline in goods producing
industries will tend to increase the male unemployment rate relative to
the female rate at least in the near term. There is no recent evidence
that the employment shift effect will offset this negative industry mix
effect. On the contrary, in 4 of the 5 years since 1978, the employment
shift has been negative. The most plausible scenario for the
female-male unemployment rate differential is for the male rate to drop
below the female rate during the current cyclical recovery, and for the
female rate to again be lower than the male rate in the next recession.
Beyond that, it seems likely that the female rate will remain below the
male rate well into the 1990’s.