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Pay Equity Empirical Inquiries (1989) / Chapter Skim
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2. Measuring the Effect of Occupational Sex and Race Composition on Earnings
Pages 49-69

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From page 49...
... The purpose of a comparable worth policy is to eliminate the effect of occupational segregation on earnings within a firm once legitimate factors that influence earnings have been taken into account. Opponents of comparable worth argue 49 that occupational segregation within a firm is not a major factor contributing to earnings disparities.
From page 50...
... The functional form of the occupational earnings equation has varied among comparable worth studies in the public sector, but the following equation typifies the approach: W0 = aO + alIO + a2 PFo + uO (1) where, the subscript 0 indicates the set of occupations; w is the occupational salary; l is the occupational job evaluation score; PF is the proportion of women in an occupation; and u is the random error term.
From page 51...
... A comparable worth policy might then eliminate the negative effect of both variables from the earnings equation. This analysis can be extended to individual earnings if we make an assumption regarding the relationship between individual and occupational earnings.
From page 52...
... Thus, it would be more appropriate to estimate separate earnings equations for each sex/race group. In addition, I would like to estimate the effect of occupational segregation on earnings within firms, since comparable worth policies ad~lress intrafirm effects of occupational segregation.
From page 53...
... The second row of Table 2-1 reports the estimated coefficients for the sex an(l race composition variables from the full regression model. The most striking result is the dramatic decline in the estimated coefficients for the proportion of minorities in an occupation after other independent variables are accounted for in the model.
From page 55...
... They were not included, however, in the final versions of the equations because they are difficult to classify as legitimate factors for differentiating salaries. Nonetheless, the estimated coefficients for the proportion of women in an occupation in the white and minority female earnings equations were not affected by the inclusion of these variables.
From page 56...
... Allocating the national earnings differentials for different sex/race groups into four components is particularly useful because it separates the effect of occupational segregation from other factors that are frequently cited as more important explanations for these earnings differences. As stated before, the goal of a comparable worth policy is to eliminate the effect of occupational segregation, which is measured by the first PAY EQUITY: EMPIRICAL INQUIRIES component described above.
From page 57...
... In summary, these findings suggest that even though differences between women and men in productivity and industrial characteristics explain about 40 percent of the national earnings disparity between women and men, another 20 percent is due to occupational segregation by sex, the portion of the earnings disparity that a comparable worth policy seeks to eliminate. Thus, this study finds that a national comparable worth policy would address a sizable component of the national sex-based earnings cli~erential.
From page 58...
... Source: Current Population Survey data tapes, May and June 1983; Bureau of the Census (1983~.
From page 59...
... In this sector, the ratio of white female to white male earnings expressed in percentage terms is 63 percent, which leaves an earnings disparity between white women and white men of 37 percentage points. Approximately 26 percent of this earnings disparity is attributable to the sex and race composition of the occupation.
From page 60...
... SUMMARY AND CONCLUSION This study argues that the purpose of a comparable worth policy is to eliminate the effect of occupational segregation by sex and race from earnings within firms. It then estimates this effect as closely as possible using a national data set, the Current Population Survey.
From page 61...
... In particular, occupational segregation by sex explains onethird of the earnings disparity between white women and white men in the public sector ancT one-fourth of this earnings gap in the nonmanufacturing private sector. But, in the manufacturing sector, it explains only 6 percent of this earnings differential.
From page 62...
... = Specific Vocational Preparation. SOURCES: Current Population Survey data tapes, May and June 1983; Bureau of the Census (1983)
From page 63...
... 3.8316 3.7799 3.2781 3.4656 S.V.P. 5.6754 5.1133 4.7283 4.6418 Strength 2.3372 1.8947 2.6721 2.0817 Physical demands 1.7245 1.4806 2.0371 1.6112 Environment 0.6049 0.1973 0.7700 0.3435 Northeast 0.2328 0.2336 0.1628 0.1365 North Central 0.2944 0.2935 0.1208 0.1365 West 0.1679 0.1753 0.2424 0.2070 Large SMSA 0.1251 0.1245 0.2609 0.2104 Medium SMSA 0.2456 0.2503 0.2710 0.2826 Small SMSA 0.3022 0.2839 0.2517 0.2896 Mining 0.0188 0.0043 0.0109 0.0026 Construction 0.0741 0.0097 0.0839 0.0043 Lumber 0.0072 0.0018 0.0193 0.0017 Furniture 0.0070 0.0042 0.0050 0.0026 Stone 0.0085 0.0039 0.0109 0.0078 Primary metals 0.0148 0.0028 0.0117 0.0035 Fabricated metals 0.0214 0.0091 0.0252 0.0070 Machinery, exe.
From page 64...
... = Specific Vocational Preparation. SOURCES: Current Population Survey data tapes, May and June 1983; Bureau of the Census (1983)
From page 65...
... (0.0311) Physical demands - 0.0122 *
From page 66...
... (0.1183) Retail trade - 0.0336 - 0.0282 0.0251 - 0.0887 (0.0530)
From page 67...
... in Log Wage Equations, by Industrial Sector Public Sector Nonmanufacturing Manufacturing White White White White White White Variable Names Males Females Males Females Males Females Constant 1.5040 *
From page 68...
... (0.0446) Physical demands - 0.0719 *
From page 69...
... p < .05. SOURCES: Current Population Survey data tapes, May and June 1983; Bureau of the Census (1983)


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