ELAINE SORENSEN”

Effect of Comparable Worth Policies on Earnings

The initial impact of comparable worth legislation on mule and female earnings is estimated using five public sector comparable worth studies. We find that women would earn an average 17 per cent more $ a comparable worth policy were implemented and men would earn an average 1 per cent more. In addition, about half of the earnings gap between women and men in the sample jurisdictions would be eliminated. We also discuss the limitations of previous analyses by examining Aldrich and Buchele’s recent empirical work.

WOMEN’S LABOR FORCE PARTICIPATION in the United States has become increasingly similar to men’s over the last three decades, and major federal legislation has been enacted to combat economic discrimination against women. Nevertheless, women’s earnings relative to men’s have remained largely unchanged: In 1983, full-time female workers earned only 64 per cent as much as full-time male workers - the same ratio as in 1955.

Proponents of comparable worth legislation argue that it is a feasible method of reducing this pay disparity. Opponents contend that such legislation at best will be ineffective in reducing the male-female earnings differential. Neither side has yet evaluated the results of comparable worth studies already performed by state and local governments to determine the policy’s effectiveness in reducing the gender-based earnings gap. This paper estimates the impact of a comparable worth policy on this pay differential by examining five public sector comparable worth studies from: Iowa, Michigan, Minnesota, Washington, and the City of San Jose.2 Similar patterns of pay inequity are found in all five locations, with the level of underpayment ranging from a low of 18 per cent to a high of 25 per cent. The paper also evaluates Aldrich and Buchele’s

*Department of Economics, University of Massachusetts, Amherst. ‘Ehrenberg and Smith (1984; 1987) examine three public sector comparable worth studies, but they

do not estimate the effect of implementing comparable worth legislation on the earnings gap between men and women.

This paper is based on research made possible by a grant from the Service Employees International Union, AFL-CIO. An earlier, abbreviated version of the paper was presented at the 1985 Meeting of the American Economic Association (see Sorensen, 1986).

INDUSTRIAL RELATIONS, Vol. 26, No. 3 (Fall 1987). 81987 by the Regents of the University of California. 0019/8676/87/1023/227/$10.00

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(1986) efforts to estimate the impact of comparable worth legislation and finds their analysis flawed by mistaken assumptions and an incorrect choice of units of analysis.

Comparable Worth: Theory and Measurement Comparable worth policy aims at eliminating the earnings dis-

parity between women and men that is associated with occupational segregation within a firm (Steinberg, 1984). Other factors which contribute to intrafirm wage differentials between women and men, such as differences in job re- quirements, are considered legitimate reasons to differentiate salaries. Com- parable worth theory predicts that occupational segregation contributes to the earnings disparty within a firm because employers practice gender-based wage discrimination against women. For example, two jobs may require com- parable amounts of skill, effort, and responsibility and have similar working conditions, but because one job is performed predominantly by women, an employer pays that job less than a job held predominantly by men.This form of discrimination depresses the salaries of female-dominated occupations relative to male-dominated ones with comparable job requirements.

Measurement. The comparable worth studies conducted by the state and local governments examined here (Iowa, Minnesota, Michigan, Washington, and San Jose) all share a similar method of measuring the effect of occupational segregation on their occupational earnings structure. They begin with a job evaluation of male- and female-dominated jobs, and each uses an “a priori” factor-point job evaluation plan. The factors usually f d into four broad categories: skill, effort, responsibility, and working conditions. Weights are applied to each factor to indicate its relative importance; both the factors and weights are selected before the evaluation begins. An evaluation committee assesses each job in terms of each factor and assigns a level of points that reflects the extent to which this factor is required on the job. Factor scores are summed for each job to produce a total point score, or job evaluation score. The second step, again shared by all of the sample studies, is an analysis of the occupational earnings of male- and female-dominated jobs as a hnction of their job evaluation scores. The studies hypothesize that the earnings structure of male- and female-dominated jobs are significantly different and that female-dominated jobs receive a lower wage than male-dominated jobs for the same job evaluation score.

The specific earnings equations vary slightly among these studies. To facilitate comparisons across studies, the following two occupational earnings equations are estimated:

Comparable Worth and Earnings I 229

where: m and f equal the set of male- and female-dominated occupations, respectively; S equals the occupational salary for each occupation; J equals the job evaluation score for each occupation; and v equals the random error term.

Male- and female-dominated jobs are defined as any occupation in which 70 per cent or more of the employees are male or female, respectively. This definition is often referred to as the “70 per cent rule” and has become the standard definition used in public sector comparable worth ~ t u d i e s . ~ The dependent variable is the occupational salary, defined as one of the salary levels within an occupation to which workers may be assigned. Generally, the maximum salary level is used to represent the occupational salary, although other steps have also been used. The job evaluation score, as noted, measures the overall requirements of a job according to established criteria.

A comparable worth policy can achieve its goal of eliminating the effect of occupational segregation on a gender-based earnings disparity by setting the occupational salaries of female-dominated jobs according to their predicted salaries from the estimated earnings equation of male-dominated jobs. In other words, a comparable worth proposal would compute the earnings of female-dominated occupations from the following equation:

where: f equals the set of female-dominated occupations; &, and A1 equal the estimated coefficients from the male-dominated occupational earnings equation; and J equals the job evaluation score for each female-dominated job.

If a comparable worth policy were implemented, workers in female-dominated jobs would receive a salary adjustment based upon the percentage difference between their predicted earnings and their actual earnings. This procedure yields considerable salary increases for workers in female-dominated jobs (increases for five sample jurisdictions are noted below). The percentage gain for female and male workers under a comparable worth policy also can be calculated by summing the percentage gain for each female-dominated job once it has been weighted by the proportion of women (men) in the occupation. The results of such calculations are reported below.

3All of the studies in this survey use this definition, except Minnesota’s investigation, which defined male-dominated occupations as any occupation with 80 per cent or more male employees.

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Results Table 1 presents the estimated male- and female-dominated

occupational earnings equations for the five studies in this analysis. The table shows that in three of the five jurisdictions, the estimated coefficient on the job evaluation score is larger in the equation for male-dominated jobs than for female-dominated jobs. Furthermore, the estimated constant term is sub- stantially larger in the equation for male-dominated jobs than for female- dominated jobs in all cases except Iowa. These differences suggest that the earnings structure of male-dominated jobs ditTers significantly from the earnings structure for female-dominated jobs.

Chow tests are conducted on each pair of male- and female-dominated equations to determine whether the estimated differences in the coefficients are statistically significant. The results, reported in Table 1, show a significant difference between the estimated coefficients for each pair of equations, in- dicating that the earnings of female-dominated jobs as a function of their

TABLE I ESTIMATED EARNINGS EQUATIONS FOR MALE- AND FEMALE-DOMINATED OCCUPATIONS

(T-VALUES IN PARENTHESES)

Dependent Constant Job evalu- - F from Studies variable term ation score R’ Chow test

233.854* 5.380*

233.085* 4.981*

149.915 .991*

36.628 ‘921’

1013.846* 3.301*

729.300* 3.521*

1105.974* 3.536*

925.248* 2.691*

1091.916* 2.789*

654.623* 3.193*

Iowa s, (6.708) (57.034) ,882 18.9

Sf (5.524) (33.468) ,694

Michigan s, (1.303) (14.622) ,758 29.1

Sf (. 430) (16.627) ,768

Minnesota S, (26.976) (26.775) ,846 44.9

sr (40.407) (38.169) ,963

San Jose S, (18.476) (13.541) .593 66.0

Sf (16.973) (10.549) .626

Washington S, (14.533) (13.159) ,789 19.3

Sf (14.945) (14.364) ,915 *Significant at the ,001 level in a two-tailed test. Source: Author’s calculations from data in: State of Iowa, “Study to Establish an Evaluation System for State of Iowa Merit Employment System Classifications on the Basis of Comparable Worth: Final Report.” Arthur Young & Company, April 1984; State of Michigan, Michigan Department of Labor, Office of Women and Work, “A Comparable Worth Study of the State of Michigan Job Classifications.” Arthur Young & Company, undated; State of Minnesota, Council on the Economic Status of Women, “Pay Equity and Public Employment.” March, 1982; City of San Jose, “Study of Non- Management Classes.” Hay Associates, undated and City of Sen Jose, “Employment Print-out.’’ August, 1984; and State of Washington, Department of Personnel, “1982 Comparable Worth Study Report,’’ January, 1983 and State of Washington, Department of Personnel and Higher Education Personnel Board, “Comparable Worth Results.” Undated.

Comparable Worth and Earnings 1 231

requirements are significantly different from the male-dominated ones. More- over, all of the R2s are quite high, ranging from .59 to .96. This implies that a large proportion of the variation in occupational salaries can be explained by the job evaluation score.

Table 2 identifies the proportion of women and men in each jurisdiction who are employed in female-dominated occupations and underpaid relative to workers in comparable male-dominated occupations. The percentage of women working in such occupations is overwhelming: It ranges from 62 per cent in Washington to 95 per cent in Minnesota, with an average figure of 79 per cent. The table shows a contrastingly small proportion of men employed in female-dominated occupations that are underpaid relative to comparable male-dominated occupations. This figure ranges from 5 per cent in San Jose to 10 per cent in Michigan and averages 8 per cent for the five jurisdictions.

Column 1 of Table 3 reports the percentage increases that workers in female-dominated jobs would receive if a comparable worth policy were implemented. The percentage gains would vary from 16 per cent in Iowa to 34 per cent in Washington. The average for the five jurisdictions would be 23 per cent. Thus, if comparable worth (as described above) were implemented, it would substantially increase the earnings of workers in female-dominated jobs.

Table 3 also reports the percentage gains for workers of both genders if a comparable worth policy were implemented. Women’s earnings would increase by an average of 17 per cent in the five jurisdictions, with a range from 11 per cent in Iowa to 20 per cent in San Jose. Men’s earnings, on the other hand, would change very little. Column 3 shows that men’s earnings would increase by an average of 1 per cent in the five jurisdictions if comparable worth legislation were implemented.

Table 4 presents the earnings ratio between full-time female workers and full-time male workers before and after the implementation of a comparable worth policy. Before such implementation, the earnings ratio ranges from 74

TABLE 2

THE PERCENTAGE OF WORKERS IN FEMALE-DOMINATED JOBS AFFECTED BY UNEQUAL PAY FOR COMPARABLE WORTH

Percentage Percentage Studies of women of men

Iowa 74.3 8.2 Michigan 81.0 10.3 Minnesota 95.3 7.6 San Jose 82.5 5.0 Washington 61.4 9.0

Average 78.9 8.0

Source: See Table 1.

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TABLE 3

PERCENTAGE GAINS FOR WORKERS IF COMPARABLE WORTH LEGISLATION WERE IMPLEMENTED

Percentage

workers in gains for gains for gains for Percentage Percentage

Studies female jobs‘ womenb menC

Iowa 15.9 11.2 1.0 Michigan 17.5 14.2 1.8 Minnesota 21.4 19.8 1.0 San Jose 25.5 20.1 1.0 Washington 33.5 17.8 2.2

Average 22.8 16.6 1.4

*Percentage gains for workers in female jobs is equal to: ?($ - Sf / Sf) * (nr / N,), where f equals the set of female- dominated occupations; .$ equals the predicted occupational salary for f ( i .e~, 61 = & + &, Jl); Sf equals the actual occupational salary; nr equals the number of workers in f; N, equals the total number of workers in female-dominated occupations. bPercentage gains for women is equal to: T(s, - S, / S,) * (nu.( / N,), where i equals the set of all occupations; S, equals the current occupational salary for i; 5, eqdals the predicted occupational salary for i under a comparable worth proposal; n, equals the number of female workers in i; N, equals the total number of female workers. ‘Percentage gains for men is equal to L(S, - S, / S,) * (n,, / N,), where i, S, , s, are defined as in (b); n,, equals the number of male workers in i; N, equal; the total number of male workers. Source: See Table 1.

TABLE 4 THE IMPACT OF IMPLEMENTING COMPARABLE WORTH

ON THE RELATIVE EARNINGS OF WOMEN AND MEN

Earnings ratio Earnings ratio before after

Studies comparable worthl comparable worthb

Iowa 74.0% 81.5% Michigan 78.7% 88.2% Minnesota 73.8% 87.5% San Jose 74.0% 88.5% Washington 76.8% 88.5%

Average 75.5% 86.8%

‘Earnings ratio between women and men before cornparable worth equals ah, where a equals average full-time female earnings, and b equals average full-time male earnings. “Earnings ratio between women and men after comparable worth equals dd , where c equals (1 + the proportional gain for female workers if comparable worth is implemented) * a. and d equals (1 + the proportional gain for male workers if comparable worth is implemented) * b. Source: See Table 1 and National Committee on Pay Equity, “The Cost of Pay Equity in Public and Private Employment.” mimeographed paper, undated.

per cent in Minnesota to 80 per cent in Michigan. The average earnings ratio for these jurisdictions is 76 per cent, indicating that full-time female workers earn, on average, 76 per cent as much as full-time male workers. After implementation, this earnings ratio would increase to 87 per cent, eliminating 46 per cent of the pay disparity between women and men in these jurisdictions.

Impact on the national earnings gap. These estimates provide a basis for predicting the initial impact of implementing comparable worth legislation on the national earnings gap between women and men. Although this estimate

Comparable Worth and Earnings / 233

is extremely rough, it has the advantage of being based on studies of individual employers’ occupational earnings structures, the currently proposed method of implementing comparable worth legislation. In contrast, other estimates have been based on national data.

Suppose that full-time female workers earn, on average, 64 per cent as much as the average full-time male worker. Assume also that firms have, on average, the same pattern of underpaying as exhibited by the sample jurisdictions and that every firm implements comparable worth according to the procedures described above. Given these assumptions, implementing a nationwide com- parable worth policy would increase women’s earnings by an average of 17 per cent and eliminate 28 per cent of the national earnings gap between women and men, raising the national female/male earnings ratio from.64 per cent to 74 per cente4

A nationwide comparable worth policy would eliminate a smaller portion of the national earnings gap between women and men than it would within individual firms (i. e., 28 versus 46 per cent) mainly because comparable worth legislation only eliminates intrafirm pay differences between comparable male- and female-dominated jobs. Interfirm differences, which are reflected in the national male/female earnings gap, remain.

These estimates measure only the initial impact of a national comparable worth policy. Implementing such legislation would prompt secondary em- ployment and earnings effects which might attenuate the initial positive impact. For example, female unemployment would likely rise and possibly reduce the gains in female earnings. Nevertheless, these estimates contrast sharply with other authors’ predictions, discussed below.

Alternative Estimates Previous empirical studies analyzing the initial effects of a na-

tionwide comparable worth policy have predicted a small positive effect on female earnings and a slight reduction in the national male/female earnings gap. For example, Mark Aldrich and Robert Buchele, in The Economics of Comparable Worth (1986), predict that a nationwide comparable worth policy would initially increase women’s earnings by no more than 14 per cent and would eliminate less than 17 per cent of the national gender-based earnings gap. Other studies of comparable worth policies have used a methodology

‘These predictions are based upon the following equation: *@Jm = (Gf/Wf) * (Wf/Wm) * (w,/*,)

where: wfMf (w,/\^N,) = the ratio of female (male) earnings before and after the implementation of comparable worth legislation; and wf/wm = the ratio of national average earnings of full-time female and male workers.

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similar to Aldrich and Buchele’s and have also predicted that national comparable worth legislation would have a small effect on female earnings (e.g., see Johnson and Solon, 1986).5

Aldrich and Buchele develop an “economist’s model” according to which the purpose of comparable worth legislation is to eliminate the effect of occupational segregation on the occupational earnings of women and men. They estimate two earnings equations with the gender composition of the occupation included as an explanatory factor to reflect the degree of occupational segregation. The dependent variables are the mean value of male and female earnings in an occupation, respectively. The other independent variables include six job/worker traits, six industrylregional control variables, and in- teractive terms between these independent variables and the proportion of women in an occupation. The two equations can be summarized as:

w, = do + d, Fj + d, Z, + d, Fj Z, + u, Wf = eo + el Fj + e, Zf + e3 Fj Zf + uf

where: w, and wf are the mean value of male and female earnings within an occupation; Fj is the proportion of women in the occupation; Z, and Zf are the mean value of the control variables for male and female workers in the occupation; Fj Z, and Fj Zf are the set of interactive terms; and u, and uf are the error terms.

Aldrich and Buchele argue that comparable worth legislation would set average male earnings in an occupation according to their estimated earnings equation, once the effects associated with the gender composition of the occupation have been eliminated from the equation. This approach would increase average male earnings by 2.5 per cent.

Aldrich and Buchele use two methods for estimating the effect of comparable worth legislation on female earnings; these yield a lower and upper bound of the policy’s effect. Predicting average female earnings in an occupation in the same manner as average male earnings ( ie. , by subtracting from the female earnings equation the effects associated with the gender composition of the occupation) provides the lower bound, according to Aldrich and Buchele. The upper bound estimate is derived by adjusting the average female earnings in an occupation with the estimated coefficients from the male earnings equation that are associated with the gender composition of the occupation. These coefficients are multiplied by the mean value of the relevant variables for female workers and the resulting term is subtracted from the female earnings

Treiman, Hartmann, and Roos’ (1984) study predicts that national comparable worth legislation will have a large effect on the gender-based earnings gap. Their approach to measuring the effect of comparable worth legislation has serious flaws, however, as noted by Aldrich and Buchele (1986).

Comparable Worth and Earnings I 235

equation. The authors use these two methods to estimate an initial increase in women’s average earnings of at least 5 per cent and possibly as much as 14 per cent under national comparable worth legislation. This would reduce the national malelfemale earnings gap by at least 3 per cent and possibly by as much as 17 per cent.

Methodologkul limitations. Three basic problems Iimit Aldrich and Buchele’s analysis. First, their predictions (cited above) assume that all female workers and most male workers, except those in occupations that completely exclude women, will benefit from comparable worth legislation. Comparable worth proposals, in contrast, generally have restricted wage gains to workers in female-dominated jobs. My analysis of the sample comparable worth studies assumes a similar restriction. Applying this assumption to Aldrich and Buchele’s analysis results in women’s earnings under a nationwide comparable worth policy increasing by as little as 5 per cent and by no more than 11 per cent.6 These estimates are considerably smaller than the average 17 per cent gain that I predicted.

The second problem is that Aldrich and Buchele rely upon the 1960 Census occupational classifications, which have been strongly criticized for their ex- tensive use of broad occupational categories referred to as “not elsewhere classified” (n.e.c.). In 1960, five of these categories (n.e.c. for professional, clerical, sales, operatives, and laborers) included more than 20 per cent of the total labor force,7 and some also included very different occupations with opposite sex compositions. For example, expediters, weighers, mail handlers, statistical clerks, counter clerks, and bilIing clerks were all included in the 1960 Census category clerical n. e.c., but the first three were held predominantly by men while the latter three were held predominantly by women. Because the n.e.c. categories include disparate types of employment, they tend to underrepresent the extent of occupational segregation in the labor force. They may also underestimate the effect of occupational segregation on earnings since the categories are too broad to capture a decline in specific occupations as they become female dominated. Aldrich and Buchele’s analysis, because it uses the 1960 Census occupations, is subject to these same underestimations.

The third problem with Aldrich and Buchele’s analysis is that they do not apply the same procedure to female and male earnings when estimating the effect of comparable worth legislation. When determining the effect on female

BThese figures are calculated by taking Aldrich and Buchele’s lower and upper bound estimates of the percentage gains from comparable worth legislation for women in female-dominated jobs and multiplying them by the proportion of women in female-dominated jobs.

These five occupational categories were subsequently divided into more than 50 occupations in the 1970 Census.