Wages ; Women - Employment ; Discrimination in employment

Randall J. Pozdena

English

Research Papers in Economics

June 8,1984
Women's Wages
It is a widely held view that women are
discriminated against in wages and employ-
ment in the marketplace. To support this
view the statistic often cited is that women
earn on average less than two-thirds ofwhat
their male counterparts earn. In addition,
other statistics show that women are not
evenly represented in all occupations.
Women holdover95 percentofnursingand
secretarial positions, for example, but less
than athird ofthe jobs in engineering, con-
struction and the technical professions. This
seeming imbalance has led some tocontend
that employers actively keep women outof
certain occupations.
These aggregate statistics are commonly
used as evidence ofwidespread discrimina-
tion against women in the marketplace.
Upon closer examination, however, that
interpretation becomes less obvious.
Indeed, available evidence largely supports
. the idea that competitive forces in the labor
market effectively combat the effects of
discrimination. This Letter examines the
paradox and criticizes some policy implica-
tions that arise from one diagnosis ofwhat
causes differences in male and female
employment situations.
Economics of discrimination
In discussing this complex issue, it is helpful
to distinguish between twotypes ofdiscrimi-
nation: discrimination based on prejudice
and statistical discrimination. In one form of
discrimination based on prejudice, employ-
ers are willing to sacrifice p'roductivity and
profits (by overpaying men or failing to hire
qualified women) to satisfy a personal pre-
judice. In another, employers discriminate
against women not because oftheir own
prejudice, but because they fear that
productivity would be adversely affected if
male employees find it uncomfortable to
work with WOmen. The second form might
be called the "male club" view of
discrimination in the workplace.
In statistical discrimination, the employer
has no desire to satisfy a taste for prejudice,
but uses the sex ofan employee (or some
other characteristic) as a proxy for produc-
tivity-related attributes that cannot be
observed easily. The employer may use the
sex of an employee as a proxy for, for
example, physical strength,mathematical
aptitude or job commitment. It may be
economically rational for the employer to
"statistically" discriminate (despite the fact
that the stereotype does not fit anyone
employee accurately), ifthe cost ofobtain-
ing more accurate measures ofthe desired
attribute are too high.
Competition and discrimination
Although such prejudice and cost-of-
information arguments are often accepted as
the explanation for male-female differences
in the labor market, it is easy to overstate
their likely importance. In a competitive
economy, there are extremely strong forces
at work to minimize their effect on wages
and employment. If afirm could hire
females who were as productive as males at
60 percentofthe male wage rate, for
example, itwould have aconsiderable cost-
advantage over its competitors and, hence, a
strong incentive to hire women at a lower
wage. Prejudicedemployers would presum-
ably be driven out ofthe marketplace by
more profitable, unprejudiced employers.
Similarly, competitive firms have an incen-
tive to avoid the arbitrary use ofstatistical
proxies; firms that devise inexpensive
means ofobtaining more accurate informa-
tion on prospective employees wiII have a
more productive work force than their
prejudiced counterparts. In acompetitive
economy, the effects ofthe formation of
"male clubs" also would be limited by the
abilityoffemales to form theirowncompeti-
tive enterprises. Although this would lead to
segregated enterprises, one would not
expect itto lead to male-female wage
differentials or segregation by occupation.n(.~\v·::~I().t1'pr dc) not
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Some paradoxes
More important than these theoretical chal-
lenges tothe conventional wisdom concern-
ing sex discrimination are some seeming
paradoxes in the statistical record offemale
labor marketperformance. Ifone believed,
for example, that there was widespread
economic discrimination against women in
the economy, significant wage differentials
wouId be expected in all workerage groups.
Yet data from aNational Science Foundation
study in 1977 show that the earnings of new
entrants to the labor market, such as recent
male and female college graduates, are
virtually identical for males and females
regardless ofthe individual's field ofstudy.
The average across all business and
engineering fields was $12,548 for males
and $12,580 for females, for example.
Employer discrimination against women
could also be expected to cause women to
escape unfair labor practices by seeking self-
employment. We thus mightexpect to see a
higher proportion ofwomen than men in
self-employment, and self-employed
women's wages to be relatively higher than
what women earn in comparable wage and
salary employment. Yet studies by Fuchs in
1960 and more recently by Moore have
failed to find such patterns. Not only do
relatively fewer females seek self-
employment, their relative wages are either
equal to or less than what they earn in the
wage and salary sector.
Statistical problems
Why then do the aggregate statistics appear
to show women at such a severe economic
disadvantage? Much ofthe explanation lies
in the job-related characteristics ofthe
worker, such as level and type ofeducation
and the amount ofwork experience accum-
ulated. In studies using publicly available
data, about two-thirds ofthe male-female
"wage gap" can be explained by such
simple workercharacteristics. Is the remain-
ing wage gap due to discrimination or
insufficient data for identifying other
important worker attributes?
2
This is an extremely difficultquestion to
answer. Sufficient data to account for all
relevant worker and job attributes exist- if
at all-only with an individual firm's
employment records. Such information,
however, is rarely made available to aca-
demic analysts. A studyby Malkiel and
Malldel ofa'major white-collar enterprise
found that male-female wage differences
were essentially explained by differences in
workerqualifications. A study by Siebert
and Sloane in Great Britain used similar
techniques (but much less detailed data) to
study the compensation practices offirms
engaged in various professional, public
service and manufacturingactivities. In only
one case (an engineering firm) was there a
wage differential unexplained by the avail-
able..data on the workers'qualifications.
The two studies suggest that economic or
statistical discrimination by employers does
notplaya majorrole in generatingobserved
wage differences in men and women.
Rather, as the model ofcompetitive labor
markets would suggest, overall, employers
make their decisions based on work-related
attributes ofthe worker.
labor force attachment
One ofthe most important characteristics of
the worker (male orfemale) is continuity of
service in the labor force. Human capital
(the knowledge and abilities we have or
acquire that are valued bythe marketplace),
Iike physical capital, deteriorates over time.
Prolonged absences from the labor market
can be expected to decrease the value of a
worker to an employer. A recent study by
Mincer and Ofek, for example, found that
each year in which a workerdid not parti-
cipate in the laborforce resulted in a 3-8
percentdeterioration in his orherwage from
what itwould otherwise have been. Since
women spend approximately three times as
much oftheir working life outside the labor
force as men, the deterioration oftheir
"human capital" may result in apparent
disparities between average male and
female wages.20
16
24
16
22
Blrlhs/1000people
26
Chart 2
MalelFemale Earnings & Child-Bearing
(1955.1982)
1.90
Yet the economic theory and research cited
here suggests that apparent wage and em-
ployment disparities between males and
females may be due less to widespread
prejudicial practices than to the simple
interaction offorces ofsupply and demand.
Ifthis were the case, "corrective" policies
such as comparable worth compensation
wouId lead to a less efficient allocation of
labor, with resultant higher levels of
unemployment and lower levels ofoutput
for the economy as a whole.
RandallJ.Pozdena
Comparable worth
It has become increasingly importantto
resolve these and other issues regarding
disparities in male-female compensation
and employment patterns. In a recent
decision in the State ofWashington, for
example, the court concluded that women
were discriminated against because the
wages paid in predominantly female occu-
pations were less than in predominantly
maleoccupationsof"comparableworth"-
that is, in occupations requiring "similar"
skills. Ifthe decision were upheld, the State
ofWashington's liabilities to its female em-
ployees would be in the billions ofdollars.
1.60 14
1955 1960 1965 1970 1975 1980 1985
measuring skill requirements across diverse
occupations. Nevertheless, using coarse
occupational categories, Polachek found
that differences in labor force participation
alone accounted for much ofthe observed
occupational "segregation." Specifically,
women's share ofprofessional positions
would increase by 35 percent and their
share of menial jobs would decrease by 25
percent ifthey had the same labor force
participation behavior as men. Although
Polachek's simpletests are hardlydefinitive,
they do point out the tenuousness ofthe
assumption that conscious employer
discrimination is the primary cause ofthe
large observed occupational differences
between the sexes.
3
60 70 50 30 40 20 10
0.8
0.7
0.9
Women who choose not to form families
should be less likely to be absent from the
Iaborforce for prolonged periods and, there-
fore, shouId experiencefewerofthe resuItant
effects on their market wage. Data from the
National Longitudinal Survey confirms this
hypothesis-single women who have never
been married have wages virtually identical
to their male counterparts.
Chart 1
Relative Participation Rates of WomenIMen '
(1984)
The major causes of reduced female labor
force participation and lower relative wages
appear to be marriage and child rearing. As
Chart 1 illustrates, the majoranomaly in the
pattern of relative male and female labor
force participation rates occurs in the
twenties and thirties, when many individ-
uals are forming families and bearing and
raising children. Female participation in the
labor market is lower relative to its trend
relationship to male participation rates. This
is consistent with the observed relationship
between earlier decisions to bear children
and subsequent earnings disparities between
men and women (Chart 2). An increase in
the birth rate appears to cause a rise in the
male-female earnings ratio on average
aboutten years later, as the women return to
the laborforce with their "depreciated"
human capital.
0.8
Rilio
1.0
"Women's work"
The uneven distribution ofmale and female
employment by occupation also may be
attributed to differences in labor force parti-
cipation propensities. Ifthe average female
worker is (or plans to be) out ofthe labor
force for an extended time, she would be
rational to seek employment in an occupa-
tion that does notdepend uponcontinuous
labor force participation to maintain job
skills. One might argue, for example, that
the skill requirements ofsecretarial, clerical
and primary school teaching positions pro-
bably are influenced less by extended labor
force detachment than, say, those ofuniver-
sity teaching or corporate management.
This is an extremely difficultproposition to
demonstrate because ofthe difficulty in55"'::> 15HI:I
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BANKING DATA-TWElFTH FEDERAL RESERVE DiSTRiCT
(Dollar amounts in millions)
(G)~<§~~\ill~dJ~ \ill~~
~(G) ~\ill~ClJI
~~dJ~<§~CQI TI~dJ~1P~~
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SelectedAssets and Liabilities
Large Commercial Banks
Amount
Outstanding
5/23/84
Change
from
5/23/84
Change from 12/28/83
Percent
Dollar Annualized
Loans, Leases and Investments1 2 179,676 - 468 3,651 5.1
Loans and Leases 1 6 160,274 - 322 4,919 7.8
Commercial and Industrial 48,637 122 2,674 14.4
Real estate 59,855 21 956 4.0
Loans to Individuals 28,042 20 1,391 12.9
Leases 4,988 - 15 - 75 - 3.6
U.S. Treasury and Agency Securities2 11,864 - 136 - 643 - 12.7
Other Securities2 7,538 - 10 - 625 - 18.9
Total Deposits 186,209 -1,679 - 4,788 - 6.2
Demand Deposits 43,121 -2,262 - 6,116 - 30.7
Demand Deposits Adjusted3 28,072 -1,245 - 3,259 - 25.7
OtherTransaction Balances4 11 ,994 - 137 - 781 - 15.1
Total Non-Transaction Balances6 131,094 720 2,109 4.0
Money Market Deposit
Accounts-Total 39,303 - 34 - 294 - 1.8
Time Deposits in Amounts of
$100,000 or more 39,442 415 1,277 8.2
Other Liabilities for Borrowed MoneyS 19,647 972 - 3,360 - 36.1
Weekly Averages
of Daily Figures
Reserve Position, All Reporting Banks
Excess Reserves (+l/Deficiency(-)
Borrowings
Net free reserves (+l/Net borrowed(- l
Weekended
OS/21/84
- 16
55
- 71
Weekended
05/07/84
89
147
58
Includes loss reserves, unearned income, excludes interbank loans
Excludes trading accountsecurities
Excludes U.S. governmentand depository institution deposits and cash items
ATS, NOW, Super NOW and savings accounts with telephone transfers
Includes borrowing via FRB, TI&L notes, Fed Funds, RPs and other sources
6 Includes items notshown separately
Editorialcommentsmay be addressedtotheeditor(GregoryTong) ortotheauthor....Freecopiesof
Federal Reserve publicationscan be obtainedfrom the Public Information Section, Federal Reserve
Bank ofSan Francisco, P.O. Box 7702, San Francisco 94120. Phone (415) 974-2246.

Women's wages

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Women's wages

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