Women, Work, and Wages Equal Pay for Jobs of Equal Value (1981) / Chapter Skim
Currently Skimming:
2 Evidence Regarding Wage Differentials
2 Evidence Regarding Wage Differentials
Pages 13-43
The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.
From page 13... ...
Moreover, although schooling has been consistently found to be closer, correlated with earnings, at every level of schooling women and black men have lower earnings than white men (Table 2~.For example, black men with some college education have lower mean earnings than white men who are high school graduates and only slightly higher mean earnings than white men who have not graduated from high school; and both black and white women who are college graduates have lower mean earnings than white men with eighth-grade educations.' The difference in income between white men and '`black and other" men who work full time all year has tended to decline over the past two decades (see Table 3~. Between 1955 and 1975, for example, about 40 percent of the difference was eliminated.
|
From page 14... ...
Over the same penod much of the racial component of the difference in income between black and other women and white men was eliminated, a fact that has reduced the overall gap but left these women in approximately the same position as white women. Since the mid-1970s, when black and other women achieved virtual panty with white women, the income dispanty vis-a-vis white men has not declined further.
|
From page 15... ...
Is x of x ~'.
|
From page 16... ...
Second, as we note below, the extent of occupational segregation the degree to which different groups hold different rather than similar jobbers greater by sex than by race, and this segregation is the very situation that evokes an interest in methods for determining the comparable worth of dissimilar jobs. Third, most of the available research on comparable worth considers sex differentials.
|
From page 17... ...
The human capital approach denves from the neoclassical economic theory of wages, which treats wages, the price of labor, like all other prices and posits that, in the absence of discrimination, equilibrium wages wall be just equal to the marginal revenue product of labor. In noneconomic terms this means that in the absence of discrimination workers wall be paid an amount exactly equal to the value of their economic contribution to a firm.
|
From page 18... ...
.3 The basic procedure in human capital studies of earnings differences between men and women is to estimate what their average earnings would be if men and women received an equal return on their human capital and the only differences in their earnings were those due to differences in the amount of their human capital, which are considered to be proxies for differences in productivity. Such estimates are then used to decompose the total difference in average earnings into that part due to differences in human capital and, presumably, productivity-and that part due to differences in the rate of return on investments in human capita~ohen assumed to represent discrimination.
|
From page 19... ...
Let us now turn to the empirical literature.' Table 4 summarizes the findings from several studies based on data from national samples of the working population that attempt to account for differences in earntngs between men and women on the basis of the characteristics of workers. In most of the studies, worker characteristics account for very little of the difference in earnings; in fact, only two of the studies can explain more than one-fifth of the difference between men's and women's average earnings in terms of differences in worker characteristics.
|
From page 20... ...
20 o lo Cat ._ CC at: to of a: · _ ._ Cal C)
|
From page 21... ...
21 et E A: a ._ V
|
From page 22... ...
WORK. AND WAGES ough of this genre of studies' including detailed measures of educational attainment, work history, on-the-job training, and attachment to the labor force for a national sample of household heads and their spouses who were in the labor force in 1975.8 This study explicitly excluded occupation as an explanatory variable in order to provide a pure test of the human capital approach.
|
From page 23... ...
/(lnU',,,,,- lnU',,~) , where AZ, Is the difference In means between white men and white women on variable i, 0,,,,,, is the regression coefficient of variable i for white men, InW,,.m is the natural log of mean hourly gages for white men.
|
From page 24... ...
Nonetheless, because of the many difficulties inherent in the human capital approach (discussed above) , because the consistency of results from these studies may resect identical flaws in the research, and because the findings concerning discrimination are so indirect (other factors failing to explain fully the difference in earnings rather than discrimination being shown to explain directly the remaining difference)
|
From page 25... ...
An index of segregation between two groups can be interpreted as the minimum proportion of one group that would have to be shifted for its occupational d~stnbution to be identical to that of the other.~° For example, in 1970, 44 percent of white women would have had to shift their occupational category for the distribution of white women across broad occupational groups to be identical to that of white men. Occupational segregation by sex has barely decreased at all among whites over the past several decades; it has decreased substantially among minorities.
|
From page 27... ...
Treiman and Terrell's csiculation (see Table 7) , based on broad occupational categories, show Mat for 3970 the index of occupational segregation by race for both men and women
|
From page 28... ...
, the solid line in Figure 1 shows the relationship between the percentage female and the median wage and salary earnings for job incumbents of both sexes. For these data, each additional percent female in an occupation results in an average of about S42 less in annual income: overall, "women's work" pays about S4,000 less per year on the average than "men's work."'3 IT It is interesting to note that occupations filled mainly (80 percent or more)
|
From page 29... ...
Solid line is simple regression of mean earnings on percent female. Broken }ins is regression of mean earnings on percent female controlling for six human capital and job characteristics see text for details.
|
From page 30... ...
; and percent female. The dotted line in Figure 1 shows the relationship between percent female and annualized median earnings, holding constant the other six vanables.tS From the substantial similarity of the solid and dotted lines in the figure it is evident that the differences among occupations with respect to these factors account for relatively little of the relationship between percent female and median earnings (although, of course, they do account for a large portion of the differences among occupations in average earnings)
|
From page 31... ...
the higher the percent female the lower the average earnings; and holding constant average earnings. the higher the percent female the higher the overall level of the factors that predict earnings.
|
From page 32... ...
, using a number of human capital vanables and the distinction between private and government wage and salary-workers, accounted for IS percent of the difference. As Table 8 shows, one reason for the lack of explanatory findings is that the differences in earnings within major occupational groups are on average nearly as large as that for the labor force as a whole.
|
From page 33... ...
And when 479 categories are used occupational segregation accounts for about 3500 percent of the difference.'9 This exercise illustrates that further analysis of occupational segregation requires much more detailed data than are currently available from the census or from national sample surveys. Studies that use the job characteristics assailable for the more detailed occupational classifications in the census and in some national samples (summarized In Table 10)
|
From page 34... ...
34 At: a ._ es c ~ o I: ._ ._ _ ~ es _ 3 ~ Cat o I: ._ c: ~ E o o ·C O ~ _ ._ _ ~ ~ o Cat ._ _ _ ~ C ~ ~ Cal Cat on ~ ~ o ._ ~ I,e ' go g I: o E ·_ _ ~ · E.° U ~ ~ ~ ha a ~ ~ .~ 0 ~ ~_ ~ [d ~ ~ o ._ ~ .0 ~ ~ O ~`0 -)
|
From page 36... ...
36 Cal o 3 i_ to V, ._ U' Cal To ~ ~ ~ .
|
From page 37... ...
37 ~_ - ~ ~ _ 3 _ E "- ~ ~ct.
|
From page 38... ...
Roos (1981) found that variables of the human capital type accounted for about 20 percent of the difference in earnings; that the addition of Duncan's socioeconomic index and prestige variables did not account for any additional portion, nor did occupational characteristics from the Dictionary of Occupational Titles; and that the addition of other occupational characteristics (industry, supervisory status, percent female, and median income of male incumbents)
|
From page 39... ...
Blau investigated the distribution of workers among firms and found that the job segregation of men and women is important in explaining wage differentials even when occupations are integrated. Using data provided by the Bureau of Labor Statistics' Blau demonstrates that within occupations that are integrated by sex, such as accounting clerk.
|
From page 40... ...
Occupational segregation by sex exists nevertheless. A number of other studies have also shown that within occupations jobs are substantially segregated across Liens, always with the result that jobs held mainly by men are paid more than jobs held mainly by women.23 Occupational segregation also exists within firms and is widely known to be common' although precise measurement of its extent is difficult because publicly available data at the establishment level are rare.
|
From page 41... ...
whether within a firm or across firms, provides an important clue to the causes of the difference in earnings between women and men. vet leases open the question of why jobs and occupations are segregated and what the exact relationship is between job segregation and pay differentials.
|
From page 42... ...
The conventional approach is to estimate, separately for men and women, an ordinary least-squares regression equation of the form Y= a ~ Ib'Xi, (1) where Y is the worker's earnings and the X' are the worker's human capital characteristics (e.g., years of school completed, years of labor force experience, amount of on-the-job training)
|
From page 43... ...
On this basis, the total earnings gap is decomposed into a portion due to differences in human capital factors and a portion due to differences in rates of return on those factors. In this example, about two-thirds of the earnings gap (~85 - 601~100 - 601)
|
Key Terms
This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More
information on Chapter Skim is available.