the impact of equal employment opportunity commission enforcement on the wages of black and white...

T H E I M P A C T O F E Q U A L E M P L O Y M E N T

O P P O R T U N I T Y C O M M I S S I O N E N F O R C E M E N T O N T H E W A G E S O F B L A C K A N D W H I T E W O M E N , 1988-1996

Sarah A. Wilhelm, Ph.D.

I N T R O D U C T I O N

Equal employment opportunity (EEO) laws have been a topic of public debate for some time. Speculation abounds about the need for such laws and the beneficiaries of such laws. However, little research is available to inform this debate. Several authors have touched upon this issue. However, timely and consistent results are unavailable, specifically with regard to the laws' impact on black and white women. This article con- t r ibutes to unders t and ing the Equal E m p l o y m e n t O p p o r t u n i t y Commission's (EEOC) role in enforcing equal employment opportunity laws and how this enforcement affects black and white women. Public opinion holds that the EEOC is unable to enforce effectively such broad legislation as Title VII because it lacks the resources to do so. Public opinion also holds that EEO laws only benefit middle-class white females and therefore do not benefit those truly in need, those for which the legislation was intended. Does enforcement of EEO laws increase women's wages? Are wages for black women and white women affected differently? This analysis, using data from the Current Population Survey and the Equal Employment Opportunity Commission, has shown public opinion to be somewhat accurate. White women do earn higher wages with stronger enforcement. Black women also earn higher wages with enforcement. Black women seem to benefit only from anti-sexism enforcement and not from anti-racism enforcement. In fact, black women benefit more from anti-sexism enforcement than white women. These results are consistent with studies done in the late 1970s.

This analysis is unique in two ways. First, this is the only recent analysis to look at the different impacts for black women and white women. This separation is essential because of the differences in labor

26 The Review of Black Political Economy/Fall 2002

market experiences by race. In addition, we would expect black women to be affected by enforcement against both race and sex discrimination, while white women should only be affected by enforcement against sex discrimination. The success of black women is not linked to the success of white women, black women are disproportionately represented in what is called the secondary job market, where wages are low, jobs menial, and benefits nonexistent. In 1980, three-fourths of black women's paid labor was in the secondary labor market; almost one third were in low- status, low-paid jobs at the bottom tier of the secondary labor market. ~ Even in jobs that are traditionally female, white women hold the higher- status jobs within that occupation, whereas black women hold the lowest. The classic example is nursing. White women are generally registered nurses and black women are generally nurses' aides. Black women are also unemployed at twice the rate of white women. 2 Occupational segregation seems to be a major limiting factor in preventing black women from making real gains in the labor market. This analysis recognizes the different experiences black and white women face in the labor market.

The second reason this analysis is unique is that data about discrimination charges are used in detail not previously available. Using measures of industry enforcement, this analysis captures decisions based on industry climate that were not previously available. In addition, measures of enforcement outcomes are included to control for success in enforcement.

B A C K G R O U N D

Title VII of the Civil Rights Act of 19643 made it illegal to discriminate in employment based on a person's race, color, religion, sex, or national origin. The EEOC was created to enforce Title VII. Since 1964, several other anti-discrimination laws have been passed that are also overseen by the EEOC .4

The EEOC is charged with resolving individual claims of discrimination and discovering areas in which systemic discrimination occurs. Sys- temic discrimination occurs on a large scale and usually takes the form of a hiring or promotion practice that systematically disadvantages mem- bers of a protected group. 5 The EEOC can have a wide-sweeping impact on the employment conditions of protected groups by winning systemic discrimination cases. The Texaco case is a recent example of the power the EEOC has to remedy discrimination on a wide scale. The EEOC found "a class-wide pattern and practice of discrimination against Afri- can-American employees with regard to the company's promotion prac-

Wilhelm 27

tices and performance appraisal process. ''6 This was the largest racial bias settlement in U.S. history, with a $176 million settlement for more than 1,300 employees. 7 However, the EEOC's limited resources also are committed to resolve individual cases. This analysis looks at the resolution of individual cases to determine if these resolutions also have wide- sweeping effects on the wages of protected groups, particularly black and white women.

L I T E R A T U R E R E V I E W

That women in the labor market face discrimination is fairly widely accepted. 8 The fact that blacks in the labor market face discrimination is less widely accepted. 9 The literature on Affirmative Action (AA) and Equal Employment Opportunity (EEO) is vast. Much of the research has focused on the impact of these programs on black men. Typically, this literature evaluates the changes in black males' employment variables relative to white males' employment variables. Most studies have found these policies to have some positive effect on the wages, employment, and occupational status of black men. 1~ One study has shown negative or negligible effects. I 1

Only a small portion of the literature deals with the impact of these policies on women. Even fewer studies address the different experiences of black women and white women. The majority of empirical work fo- cuses on comparing all women to white men. The evidence in the majority of these studies shows that EEO and AA policies have had at least some positive impact on women's employment and wages. 12 Articles showing negative or negligible effects are those of Goldstein & Smith, Heckman & Wolpin, and Leonard. 13

Beller studied the correlation between EEOC enforcement and women's wages, with separate analysis for black and white women. 14 Beller con- cluded that the effect of enforcement based on sex discrimination on the earnings of all females is more significant than the effect of enforcement based on race discrimination on the earnings of black females. Beller's results regarding the impact of a positive resolution for the employee of a discrimination charge were inconclusive. Beller's analysis is now more than twenty years old. The current analysis updated Beller by including similar proxies for enforcement, but supplements them with data from the EEOC that have not been used previously.


DISCRIMINATION AND TH E E E O C

The EEOC's ultimate goal is to eliminate discrimination in employment decisions by investigating individual charges and pursuing cases of systemic discrimination. Figure 1 shows the flow of individual charges through the EEOC and the possible outcomes of charges. The EEOC's effect on discrimination can be manifest in two ways: directly and indi- rectly. Direct effects are the changes in employment conditions experi- enced by individuals who are directly involved in discrimination cases. A woman wins a sexual discrimination case against her employer with the help of the EEOC and her wages are increased. If a competitor of her employer observes this event, she or he may raise the Wages of female employees to avoid having to face discrimination charges in the future. This action is an example of an indirect effect of EEOC enforcement activities.

D I R E C T E F F E C T S OF T H E E E O C A C T I V I T I E S

The effectiveness of the EEOC is closely tied with its record of enforcing anti-discrimination laws. The EEOC has been accused of not fully investigating charges that it dismisses as no cause; that is, no evidence of discrimination was found. The General Accounting Office found that in six EEOC district offices that were investigated, 41% to 82% of the charges closed with no-cause determinations that were not fully investigated. 15 The EEOC also has been accused of issuing right-to-sue letters without investigating or attempting to reach a settlement. If the EEOC does not finish investigating a charge after 180 days, or if it anticipates not being able to do so, it must issue a right-to-sue letter. The EEOC has had a large backlog of charges; in 1992, cases were taking an average of 292 days to resolve. 16 This practice increases the uncertainty of both the outcome and the costs to the individual.

I N D I R E C T E F F E C T S OF T H E E E O C A C T I V I T I E S

The EEOC was created to combat wage discrimination and to create employment opportunities for women and minorities. The indirect effects of EEOC are those changes that occur in the employment status of protected groups through employers changing their behavior to avoid punishment for noncompliance. With the understanding that enforcement is

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not perfect, employers must weigh the costs of compliance against the costs of avoiding punishment. 17 Costs of compliance are the costs of not discriminating, including equal pay and hiring for protected groups. These costs may be in the form of real costs (a higher wage bill) or perceived costs such as Becker's taste for discrimination. ~8 The costs of avoiding punishment include time and energy spent fighting a discrimination charge weighed by the likelihood of being caught. If employers perceive the costs of avoiding punishment to exceed the costs of compliance, they will comply by not discriminating. Employees with less bargaining power than other employees should expect a smaller or nonexistent change in their employment conditions based on successful enforcement.

Alternatively, Edelman, Uggen & Erlanger argue that employers adopt internal grievance procedures as a response to threats of enforcement. 19 Employers respond to the "rational myth" that the establishment of grievance procedures will insulate them from penalties. Whether these grievance procedures change the earnings of protected groups is not clear. However, of the 247 businesses that Edelman surveyed, 184 (74%) had not adopted grievance procedures, z~ This indicates that grievance procedures are not widespread in businesses and thus do not represent a na- tionwide response to EEOC enforcement.

Leonard stated that the major contribution of the EEOC has been to establish legal precedents in the enforcement of Title VII in the courts, z l Individual claimants can then use these precedents in private litigation. Thus, it is the establishment of legal principles rather than the direct relief to claimants in which the EEOC has made its mark. Leonard cited Griggs v. Duke Power as an example, since it placed the burden on employers to avoid the appearance of discrimination. Leonard's opinion is persuasive in light of the criticisms of the EEOC. The likelihood of punishment for employers is so low that perhaps the expected costs of punishment approach zero. On the other hand, Williams & Spriggs are skeptical that courts will offer any solutions. District courts and the Supreme Court have shown time and again that they recognize only equality before the law and accept outcomes as reflections of the abili- ties and preferences of market agents. Further they argue that courts see "only 'color,' not racialized and gendered social subjects and class relations". 22

All of the above theories on how EEOC enforcement influences employer behavior may result in improved labor market outcomes for protected groups. However, the link may be quite indirect and therefore, weak. It is the testing of this link that is the purpose of this paper.

Wilhelm 31

H Y P O T H E S I S

We would expect that increased enforcement efforts by the EEOC would lead employers to pay higher wages to both black and white women in an effort to avoid investigation and punishment from the EEOC. Employers could respond in other ways to avoid penalties: they could hire more women, promote more women, adopt grievance procedures, etc. These actions could also increase women's wages.

Employers' responses to EEOC enforcement will be influenced by two factors 1) the likelihood of having a charge filed against them, and 2) the chances of being punished based on the EEOC's record of successful enforcement. Thus both the likelihood of having a charge filed against them and the likelihood of that charge turning into a penalty for the employer will influence how the employer pays women. While we may expect more charges to increase women's wages, this is not necessarily the case. Only when those charges are likely to result in an employer penalty will charges cause employers to respond. Thus, it is only in the context of strong enforcement that charges will influence employers' behavior.

We would expect, when controlling for enforcement, that white women's wages would increase when enforced sex charges increase. We would also expect black women's wages to increase but not by as much, due to their lesser bargaining power. Black women's wages should also increase with enforced race charges while white women's wages should not be affected by race charges.

M E T H O D

This analysis is unique in two ways. First, this is the only recent analysis to address separately the impact of EEO enforcement on black women and white women. As discussed above, the labor market experiences of women vary greatly by race. Thus it is expected that the effects of anti-discrimination laws will also vary by race.

Second, this analysis is unique in that data about discrimination charges and enforcement outcomes are used in detail not previously available. Other authors have looked at state levels of discrimination charges. Charges by industry were used in this analysis, based on the hypothesis that reactions to enforcement are much stronger on an industry level than on a state level. That is, employers respond to enforcement that occurs in their industry. Manufacturing companies are aware of and concerned about punishment of other manufacturers, regardless of geographic proximity.


The assumption is that employers make decisions on the basis of industry climate rather than labor market climate. If this assumption is incorrect, we should see no connection between industry charges and wages.

Measures of enforcement outcomes move us closer to a true proxy for enforcement. Not only are the number of charges filed important, but also what becomes of those charges is informative. Only when some charges yield positive outcomes do our hypothesis about employer responses make sense.

The years 1988-1996 were chosen to represent a range of Presidential acceptance of the purpose of the EEOC, which would influence both current and future enforcement capabilities (primarily through budget appropriations).

I estimated the wage equation as a function of human capital and other demographic variables and policy variables. A wage equation supple- mented with EEOC enforcement variables displays the connection between women's wages and the efforts of the EEOC to enforce Title VII. Wage equations are common, and most of the variables used in this analysis are standard, with separate estimates for black women and white women. Heckman's sample selection correction method was used to cor- rect for sample selection bias. 23 Thus the wage equation measures changes in women's absolute rather than relative wages, for two reasons. First, increases in women's wages are likely to be connected to increases in women's relative wages. As wages were on average falling during this time period, an increase in women's wages is unlikely to be associated with a decline in relative wages. 24 In addition, a decrease in men's wages would bring an increase in women's relative wages, with no true gain for women. Second, while increases in relative wages have real impacts on equitable treatment, the purpose of this paper is to measure absolute gains in women's economic status.

DATA

The Current Population Survey March Annual Demographic File pro- vides individual level information on wages and other pertinent labor market variables. I used years 1988-1996, merged. Supplemental data acquired from the EEOC National Database regarding charges and charge resolutions provide the measures of EEOC enforcement. These data are different from the data used by other authors, as they provide charge information by industry (single digit) as well as by basis. Bases include race, sex, national origin, retaliation, religion, and "other."

Wilhelm 33

DEPENDENT VARIABLE

Average hourly earnings are calculated in 1988 dollars from annual earnings, weeks worked per year, and hours worked per week, for the years 1988-1996. The dependent variable is the natural log of average hourly earnings.

HUMAN CAPITAL AND OTHER DEMOGRAPHIC VARIABLES

The variables used in this analysis are standard. In general, the human capital variables control for individual characteristics, job characteristics, and conditions in the local labor market. Estimating separate equations will control for race and sex. Education is controlled for by dummy variables based on years of schooling. Experience is calculated as age minus schooling minus five. While this calculation of experience has been argued to be less accurate for women, including controls for number of children should compensate for inaccuracies in the experience variable. Dummy variables are created for four levels of employer size, based on number of employees. Employers with more than one hundred employees are required to report the demographics of their labor force to the EEOC. In addition, large employers tend to have more formalized and regulated personnel processes. "Or simply by being large they may escape the familial or tribal tendencies of small work forces. ''25 Thus, | expect larger employers to pay higher wages to women and minorities. The means all the human capital and other demographic variables are reported in Table 1.

A labor force selection correction is necessary because sample selection bias results from missing independent variables. The wages of those women who have chosen not to participate in the labor force are missing from the analysis. Heckman finds that a control for sample selection bias increases the explanatory power of the wage equation. 26 This analysis uses a Heckrnan maximum likelihood equation (Heckit) to control for sample selection bias.

THE POLICY VARIABLES

The variables used to measure the extent of EEOC enforcement include:

�9 Charges filed by basis, industry, and year �9 Percent of charges that result in successful conciliations, by year �9 Percent of charges that result in successful settlements, by year


TABLE 1 Means of All Variables Used in Estimations

Variable

White Black Women Women

N=158430 N=20946

Log of Real Hourly Wage Married MSA residence Central city residence Experience Experience squared Region - Midwest Region - South Region - West Unemployment <25 employees 25-99 employees 100-499 employees 500-999 employees Occupation - executive, administrative and managerial Occupation - professional specialty Occupation - technicians and related support Occupation - sales Occupation - administrative support Occupation - private household service Occupation - protective service Occupation - precision production, craft, repair Occupation - machine operators, assemblers, inspectors Occupation - transportation, material moving Occupation - handlers, equipment cleaners, etc. Occupation - farming, forestry and fishing Sex charges (log) Sex charges lagged 1 year (log) Sex charges lagged 2 years (log) Sex-wage charges (log) Sex-wage charges lagged 1 year (log) Sex-wage charges lagged 2 years (log) Sex-promotion charges (log) Sex-promotion charges lagged 1 year (log) Sex-promotion charges lagged 2 years (log) Race charges (log)

1.959 1.895 0.587 0.400 0.753 0.856 0.207 0.496

19.465 20.388 527.374 552.100

0.248 0.169 0.300 0.551 0.210 0.069 5.469 5.873 0.195 0.113 0.137 0.107 0.175 0.158 0.072 0.079 0.145 0.090 0.174 0.126 0.040 0.038 0.100 0.061 0.298 0.277 0.008 0.014 0.005 0.014 0.025 0.026 0.071 0.110 0.007 0.010 0.015 0.020 0.004 0.002

-1.062 -1.037 -1.107 -1.083 -1.167 -1.144 -3.236 -3.208 -3.209 -3.177 -3.214 -3.181 -3.592 -3.524 -3.733 -3.663 -3.862 -3.790

0.751

~onKnued)

Wilhelm 35

TABLE 1 (continued)

Variable

White Black Women Women

N=158430 N=20946

Race charges lagged 2 years (log) Race charges (log) Race-wage charges lagged 1 years (log) Race-wage charges lagged 2 years (log) Race-promotion charges (log) Race-promotion charges lagged 1 years (log) Race-promotion charges lagged 2 years (log) Successful settlement Withdrawal with benefit Successful conciliation No cause determinations Administrative closures State law covers 1+ employees State law covers 2-14 employees State law covers 15+ employees Budget variation Missing commissioners CPS Weight Female Headed Households Number of Children under 6 Number of children from 6-18 Other income Age

0.726 - 1.602 -1.539 -1.517 -1.412 -1.526 -1.630

.100 .100

.072 .072

.011 .011

.533 .533

.274 .274

.218 .213

.474 .344

.274 .334 -1.013 -0.887 5.818 5.798

.994 1.202

.360 .574

.177 .217

.498 .626 29655.21 19445.83

38.802 39.281

�9 Percent of charges that result in withdrawal of charge with benefits, by year

�9 Percent of Charges that result in no cause determinations, by year �9 Percent of charges that result in administrative closures, by year �9 Missing commissioners of the EEOC in a given year �9 EEOC budget fluctuation from eleven-year trend (in millions)

The correlations of the policy variables are reported in Table 2. Other authors have used a variety of means to attempt to isolate the effects of Title VII and EEOC activity. Some have included independent variables with which they hoped to proxy enforcement such as:


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Wilhelm 37

1. The expenditures on Title VII enforcement; 27 2. The number of successful settlements of cause determinations; 28 3. The number of discrimination charges filed and accepted by the

EEOC; 29 4. The number of Title VII class action lawsuits; 3~ 5. The number of EEOC wage and employment discrimination com-

plaints.31

The last four of these variables may be not only the commitment of the EEOC to prevent discrimination but also indices of increased discrimination. Complaint variables confuse changes in incidence of discrimination with changes in enforcement agency initiative and authority. Further- more, Shulman argues that charges must reflect discrimination. If charges do not reflect discrimination, then there should be no connection between employment variables and charges. 32 The alternative explanation, job losses or low wages that were not caused by discrimination led to charges, assumes blacks and women systematically perceive discrimination where none exists. Shulman argues this assumption would be difficult to justify, compared to the alternative that blacks and women are responding to reality. This rings especially true in light of the lag times and small likelihood of a charge resulting in a benefit.

This analysis avoids this endogeneity concern by lagging the charge variables. After controlling for current charges, past charges become a better proxy for EEOC enforcement. Charges in the past certainly would not be due to current discrimination. Insofar as discrimination may be recurring in an industry, it is controlled for by including current charges. An industry may be prone to discrimination. Current and past charges reflect the discrimination in that industry. However, once current charges are controlled for, the fact that this is a discriminatory industry is included in the estimation, and any additional information provided by past charges is not a reflection of this industry being discriminatory but in- stead new information on enforcement.

EEOC charges are available by state and by industry (but not by state and industry). The analysis uses charges by industry, under the assumption that employers are more reactive to the actions of their direct com- petitors than other companies they may be associated with by geographic area. In addition, Leonard found that industries that discriminate against blacks also discriminate against women. 33 Thus, some industries may be "bad" industries in terms of discrimination. Geographic differences in


anti-discrimination attitudes and enforcement are controlled for in re- gional and state variables.

The charge variables for an individual woman are the charges filed under the basis of sex in her industry of employment and, if she is black, a separate variable for charges filed under race for her industry. Charges will be normalized by the number of women in that industry for sex- based charges and by the number of blacks in that industry for charges based on race. These variables will represent the number of charge fil- ings per thousand of individuals eligible to file such a charge, logged. The charge variables will be included for the past two years, allowing for lag time in employer adjustments. Thus the expectation is that a woman in the 1996 CPS will be affected by charg'es in her industry from 1994- 1996.

The percent of charges that result in successful conciliations (see figure 1) reflects those charges that the EEOC investigates, finds reasonable cause to expect discrimination, and arrives at a conciliation agreement with the employer. Charges that result in successful settlements are those charges that the employer settles before the EEOC has finished investigating. Charges that result in withdrawal of charges with benefits are those charges in which the employee withdraws the charge and receives a benefit from the employer. These three variables indicate resolutions that provide a benefit to the charging party. No-cause determinations are completed investigations in which the EEOC finds no cause to expect discrimination has occurred. Administrative closures occur before investigation, due to a variety of circumstances such as no jurisdiction, charging party not cooperating, and others. The last two resolution variables do not result in a benefit for the charging party. Unsuccessful conciliations were not included in the estimation, as the numbers were so small and fairly stable. The resolution variables are at the national annual level and are reported in Table 3.

Missing commissioners are included under the assumption that when the agency does not have complete leadership, it will not be as effective. When a government agency lacks leadership, the amount of work accom- plished diminishes. The fluctuations in the budget from the eleven-year average indicate the support, literal and figurative, that the agency receives from the legislature and executive branches. The assumption that increases in the budget will improve an agency's performance is not always valid. We can imagine easily an agency that has reached a peak in performance and additional money may have negative or miniscule re-

Wilhelm 39

TABLE 3 Title VII Resolutions* by the EEOC in Percentages

Withdrawal Successful Successful Unsuccessful "No cause" Administrative Year with benefit settlement conciliation conciliation determination closures

1987 5.9 10.6 0.9 0.9 46.9 34.8 1988 6.6 11.7 1.0 1.0 50.5 29.2 1989 7.0 12.1 1.2 0.9 52.1 26.8 1990 8.2 11.9 1.1 1.8 53.2 23.7 1991 7.3 12.3 1.0 1.0 54.0 24.4 1992 7.5 10.1 1.0 0.9 54.2 26.3 1993 7.9 9.1 1.1 0.8 53.9 27.1 1994 7.9 8.8 1.3 1.1 50.2 30.7 1995 6.8 7.1 0.9 0.7 53.1 31.4 1996 5.7 6.4 1.0 0.9 58.6 27.3

Source: U,S. Equal Employment Opportunity Commission National Database *Resolutions include both EEOC and FEPA resolutions.

turns. However, the EEOC has historically been underfunded, as evi- denced by the large backlog of cases. Thus the assumption that more money will improve enforcement is not unrealistic. The missing commis- sioner and budget variation variables are at the national, annual level. Table 1 presents the means for all variables, and Table 2 presents the correlation of the policy variables.

RESULTS

The results of the Heckit, OLS and Heckit with year controls rather than annual policy variables are reported in Tables 4 and 5 (results of the probit are reported in Table 6). For both black and white women, the selection correction variables used in the Heckit model are significant. Rho is estimated at -0.870 and -0.894 for white women and black women respectively. Rho measures the correlation between the error term in the wage equation and the error term in the reservation wage equation. The fact that the correlation is significantly different from zero strongly sup- ports the use of the Heckit model over OLS. There is no substantial change in the coefficients or their significance when using OLS. Like- wise, the Heckit with year controls has similar coefficients on the charge variables. The similarity of the coefficients using year controls to the coefficient using annual enforcement data may indicate that the annual


TABLE 4 Estimations of Coefficients (Standard Errors) for All Black W o m e n

Variable Heckit OLS

Heckit with year controls

Intercept 3.166" 0.570 1.744"** (1.937) (1.744) (0.079)

Married -0.167"** 0.038*** -0.167"** (0.010) (0.008) (0.010)

MSA residence 0.005 0.143"** 0.006 (0.015) (0.012) (0.015)

Central city residence 0.049*** -0.018"* 0.049*** (0.010) (0.009) (0.010)

Experience 0.026*** 0.027*** 0.026*** (0.001) (0.001) (0.001)

Experience squared 0.000"** 0.000"** 0.000"** (0.000) (0.000) (0.000)

Region - Midwest -0.037** -0.118"** -0.037** (0.017) (0.015) (0.017)

Region - South -0.148"** -0.177"** -0.148"** (0.013) (0.012) (0.013)

Region - West 0.004 -0.026 0.003 (0.020) (0.018) (0.020)

Unemployment 0.021"** 0.008** 0.021"** (0.004) (0.003) (0.004)

<25 employees -0.244*** -0.280*** -0.243*** (0.014) (0.016) (0.014)

25-99 employees -0.178"** -0.207*** -0.178"** (0.014) (0.015) (0.014)

100-499 employees -0.121"** -0.122"** -0.120"** (0.010) (0.011) (0.010)

500-999 employees -0.079*** -0.081"** -0.078*** (0.014) (0.015) (0.014)

Occupation - executive, administrative and managerial 0.455*** 0.392*** 0.455***

(0.063) (0.074) (0.064) Occupation- professional specialty 0.473*** 0.394*** 0.474***

(0,063) (0.074) (0.064) Occupation - technicians and 0.369*** 0.320*** 0.370***

related support (0.064) (0.075) (0.065) Occupation - sales 0.130"* 0.027 0.130"*

(0.064) (0.075) (0.066)

(continued)

Wilhelm 41

TABLE 4 (continued)

Variable Heckit OLS


Occupation - administrative support

Occupation - private household service

Occupation - protective service

Occupation - other service

Occupation - precision production, craft, repair

Occupation - machine operators, assemblers, inspectors

Occupation - transportation, material moving

Occupation - handlers, equipment cleaners, etc.

Education

Year= 1989

Year= 1990

Year= 1991

Year= 1992

Year= 1993

Year= 1994

Year= 1995

Year=1996

Withdrawal with benefit

Successful settlement

0.216"** (0.062) -0.197"** (0.072) 0.356***

(0.072) -0.023 (0.062) 0.206***

(0.065) 0.087

(0.062) 0.231"**

(0.O75) 0.106

(0.O71 ) 0.060***

(O.0O2)

4.195 (2.821) -0.683 (t.953)

0.163"* (0.073) -0.302*** (O.084) 0.265***

(0.082) -0.108 (0.073) 0.129"

(0.077) 0.012

(0.073) 0.114

(0.088) -0.006 (0.081) 0.061 ***

(0.002)

7.847** (3.052) 0.980

(2.I75)

0.217"** (0.063) -0.198"** (0.073) 0.358***

(0.073) -0.022 (0.063) 0.207***

(0.066) 0.088

(0.O63) 0.232***

(0.076) 0.106

(0.072) 0.060***

(0.0O2) -0.045*** (0.016) -0.027 (0.017) -0.055*** (0.016) -0.037** (0.017) -0.060*** (0.020) -0.115"** (0.018) -0.107"** (0.018) -0.144"** (0.019)

~on~nue~

42 The Review of Black Political Economy/Fal l 2002

T A B L E 4 (continued)

Variable Heckit OLS


Successful conciliation -17.147"** -11.972" (6.327) (6.993)

"No cause" determinations -2.147 -0.314 (1.786) (1.985)

Administrative closures - 1.325 0.279 (1.660) (1.849)

Budget variation 0.004*** 0.006*** (0.001) (0.002)

Missing commissioners -0.004* -0.005** (0.002) (0.002)

Sex charges, current 0.054*** 0.057*** (0.010) (0.011)

Sex charges lagged 1 year 0.072*** 0.076*** (0.011) (0.011)

Sex charges lagged 2 years 0.056*** 0.051"** (0.012) (0.012)

Race charges, current -0.090 -0.119 (0.067) (0.074)

Race charges lagged I years -0.081 -0.040 (0.062) (0.070)

Race charges lagged 2 years -0.047 -0.037 (0.054) (0.059)

N 65129 20946 R squared .3442 Log likelihood - 1.07e+ 10 Atanh rho - 1.443"**

(0.035) Ln sigma -0.307***

(0.016) Rho -0.894

(O.OO7) Sigma 0.736

(0.012) Lambda -0.658

(0.015)

0.050*** (0.010) 0.071"**

(0.011) 0.063***

(0.012) -0.124" (0.068) 0.005

(0.069) -0.095* (0.057) 65129

- 1.07e+ 10

-1.443"** (0.035) -0.307*** (0.016) -0.894 (0.007) 0.736

(0.012) -0.658 (0.015)

*10% significance. **5% significance. ***1% significance.

Wilhelm 43

TABLE 5 Estimations of Coefficients (Standard Errors) for All White Women

Variable Heckit OLS


Intercept 2.169"** -0.197 1.121"** (0.632) (0.686) (0.034)

Married -0.017"** 0.041"** -0.017"** (0.004) (0.003) (0.004)

MSA residence 0.098*** 0.170"** 0.098*** (0.004) (0.004) (0.004)

Central City residence -0.001 -0.004 -0.001 (0.004) (0.004) (0.004)

Experience 0.033*** 0.030*** 0.033*** (0.000) (0.000) (0.000)

Experience squared 0.000"** 0.000"** 0.000"** (0.000) (0.000) (0.000)

Region - Midwest -0.084*** -0.093*** -0.083*** (0.005) (0.005) (0.005)

Region - South -0.136"** -0.137"** -0.136"** (0.004) (0.004) (0.004)

Region -West -0.046*** -0.070*** -0.045*** (0.005) (0.005) (0.005)

Unemployment 0.034*** 0.016"** 0.034*** (0.001) (0.001) (0.001)

<25 employees -0.214"** -0.242*** -0.214"** (0.004) (0.005) (0.004)

25-99 employees -0.144"** -0.149"** -0.144"** (0.004) (0.005) (0.004)

100-499 employees -0.074*** -0.071"** -0.074*** (0.004) (0.004) (0.004)

500-999 employees -0.027*** -0.023*** -0.027*** (0.005) (0.006) (0.005)

Occupation - executive, 0.403*** 0.452*** 0.402*** administrative and managerial (0.030) (0.033) (0.030)

Occupation - professional specialty 0.417"** 0.445*** 0.416"** (0.030) (0.033) (0.030)

Occupation - technicians 0.363*** 0.417"** 0.361"* and related support (0.031) (0.033) (0.031)

Occupation - sales 0.156"** 0,170"** 0.155"** (0.030) (0.033) (0.030)

(continued)


TABLE 5 (continued)

Variable Heckit OLS


Occupation - administrative support

Occupation - private household service

Occupation - protective service

Occupation - other service

Occupation - precision production, craft, repair

Occupation - machine operators, assemblers, inspectors

Occupation - transportation, material moving

Occupation - handlers, equipment cleaners, etc.

Education

Year= 1989

Year= 1990

Year=1991

Year=1992

Year= 1993

Year=1994

Year=1995

Year=1996

Withdrawal with benefit

Successful settlement

0.170"** 0.219"** (0.030) (0.033) -0.313"** -0.346*** (0.038) (0.042) 0.212"** 0.245***

(0.036) (0.040) -0.050* -0.032 (0.030) (0.033) 0.238*** 0.273***

(0.031) (0.034) 0.052* 0.083**

(0.030) (0.033) 0.100"** 0.114"**

(0.035) (0.038) -0.008 0.004 (0.032) (0.035) 0.070*** 0.066***

(0.001) (0.001)

3.955*** 6.626*** (0.880) (0.966) -0.266 1.308" (0.684) (0.749)

0.169"** (0.030) -0.314"** (O.O38) 0.210"**

(0.036) -0.051 * (O.030) 0.236***

(0.031) 0.050

(O.O30) 0.098***

(O.O35) -0.010 (0.032) 0.070***

(o.001) -0.041 *** (0.006) -0.051"** (0.006) -0.060*** (0.006) -0.055"** (0.006) -0.075*** (0.006) -0.097*** (0.006) -0.136"** (0.007) -0.135"** (0.007)

(continued)

Wilhelm 45

TABLE 5 (continued)

Variable Heckit OLS


Successful conciliation -6.410"** (2.296)

"No cause" determinations -1.890"** (0.650)

Administrative closures - 1.019* (0.604)

Budget variation 0.005*** (0.000)

Missing commissioners -0.004*** (0.001)

Sex charges, current 0.054*** (0.004)

Sex charges lagged 1 year 0.036*** (0.004)

Sex charges lagged 2 years 0.031 *** (0.003)

N 499380 R squared Log likelihood -6.58e+10 Atanh rho - 1.332***

(0.022) Ln sigma -0.324***

(0.011) Rho -0.870

(0.005) Sigma 0.723

(0.008) Lambda -0.629

(0.01 l)

-1.221 (2.505) 0.072

(0.706) 0.548

(0.657) 0.006***

(0.001) -0.003*** (0.001) 0.055***

(0.004) 0.038***

(O.O04) 0.037***

(0.004) 158430

.3228

0.051"** (0.004) 0.035***

(0.004) 0.037***

(O.0O4) 499380

-6.58e+10 -1.333*** (0.022) -0.324*** (0.01 l) -0.870 (0.005) 0.723

(0.008) -0.629 (0.011)

*10% significance. **5% significance. ***1% significance.

46 The Review of Black Political Economy/FaU 2002

TABLE 6 Coefficients (Standard Errors) from Probit

Variable Black Women White Women

Intercept -0.516"** 0.027 (0.045) (0.017)

Married 0.852*** 0.862*** (0.022) (0.011)

Female Headed Household 0.438*** 0.755*** (0.021) (0.011)

MSA residence 0.304*** 0.141"** (0.016) (0.005)

Central City residence -0.146"** -0.027*** (0.012) (0.005)

Age -0.011"** -0.025*** (0.000) (0.000)

Children <6 -0.231"** -0.298"** (0.010) (0.006)

Children >6, < 18 -0.070"* * -0.125"** (0.005) (0.003)

Other Household Income 0.000 0.000"** (0.000) (0.000)

State law covers l+ employees 0.057*** 0.026** (0.018) (0.011)

State law covers 2-14 employees -0.023 -0.048*** (0.018) (0.010)

State law covers 15+ employees 0.028* -0.001 (0.016) (0.010)

Region - Midwest -0.149"** -0.022*** (0.019) (0.006)

Region - South -0.071"** -0.028"** (0.017) (0.006)

Region - West -0.044* -0.048"** (0.023) (0.006)

Year, scaled 0.007*** 0.014"** (0.002) (0.001)

Unemployment -0.014"** -0.028"** (0.005) (0.002)

Sources: U.S. Equal Employment Opportunity Commission, Theories of Discrmination, 1995 U.S. Equal Employment Opportunity Commission, Annual Reports 1980-1995.

Wilhelm 47

fluctuation in the strength of enforcement is captured simply by the year variable, rather than the variation in various enforcement measures. In addition, enforcement variables appear to have only sporadic significant impact on charges. Thus, the preferred model (and the one discussed hereafter) is the Heckit with year controls. The consistent results on the charge variables are robust. The human capital and other demographic variables have coefficients as expected.

E F F E C T S OF RACE D I S C R I M I N A T I O N C H A R G E S

The results in Column 3 of Table 4 show two separate patterns for charges based on race and charges based on sex for black women. Race charges are not strongly correlated with wages. 34 This is true for current charges and charges lagged one and two years.

Belier also found no significant correlation between race charges and wages for black women. 35 She included only race charges filed by women. I have included all race charges filled by men and women. Both Beller's and my findings indicate that black women's wages are not correlated with race charges, current or past, despite the fact that in the years 1990- 1996 between 40 and 50 percent of race discrimination charges were filed by women. 36

EFFECTS OF SEX DISCRIMINATION CHARGES

Both black and white women's wages have similar correlations with charges based on sex. Both wages and charges are logged, so coefficients can be treated as elasticities. Sex discrimination charges are positively correlated with both black and white women's wages. This is true for current charges as well as for charges lagged one and two years. Current charges are positively correlated with current wages. That is, those industries in which wages are high see more charges. While one might expect current charges to be higher in low-wage industries, it may only be that only those who feel they have bargaining power will file charges.

Positive coefficients on charges lagged one and two years indicate that the more charges an industry has had in the past, the higher the wages are. This is true after controlling for the fact that more charges occur in high-wage industries. Thus, good industries get better. The coefficients are larger for black women than white women. Working in an industry that has a high number of sex discrimination charges has a stronger positive effect on black women's wages than on white women's wages.


This is inconsistent with the hypothesis stated above. This result also is inconsistent with the popular opinion that white women benefit more from this legislation and its enforcement. These results are encouraging, that black women are benefiting more than white women. One could argue that black women have suffered more than white women from discrimination and thus are benefiting most from attempts (however mea- ger) to eliminate that discrimination.

The magnitudes of the coefficients on sex discrimination charges are small. The elasticities for black women is .071 and .063 for charges lagged one and two years respectively. The elasticities for white women are .035 and .037. However, based on the indirect nature of this proxy for enforcement, the small size of the coefficients is of minimal concern. Belier found the elasticities for sex discrimination charges to be 1.8 and 2.5 in the periods 1967-1972 and 1972-1974. 37 My results show a much smaller effect than Belier's, which may be due to an increased understanding by employers over the past twenty years on the effectiveness of enforcement.

CONCLUSION

The most encouraging result of this article is that women can make a difference by filing sex discrimination complaints. This result is consistent with Beller's results from a similar analysis in 1977. An increase in complaints leads to an increase in wages for all women. Employers do respond to the threat of an EEOC investigation of sex discrimination (regardless of outcomes) by improving wages for both black women and white women. The same is not true for filing race discrimination complaints. Race discrimination charges were not significantly correlated with black women's wages. This result may be partially due to the fact that all race discrimination charges are included in the analysis. Race discrimination charges filed by black men may not affect black women's wages. However, Belier finds the same result, although her analysis included only race charges filed by women. 38 Therefore, inclusion of race discrimination charges filed only by women did not provide additional information. Other possible explanations for this outcome involve the possibility that the enforcement capabilities of the EEOC are poorly matched with the strength and nature of racism in this country.

The EEOC is responsible for enforcing Title VII by processing individual charges and discovering areas where systemic discrimination occurs. The area of individual charges has been seen as a commitment the

Wilhelm 49

EEOC must fulfill, but that does not have any widespread effects on discrimination. These results contradict this opinion. While a t tempts to discover systemic discr iminat ion m a y have larger, w ide - sweep ing effects, individual sex charges benefi ts do not accrue only to the individuals who file them.

This analysis shows that public opinion of the E E O C m a y not be accurate. Black women are benefi t ing fo rm its en forcement activit ies at least to the same extent white w o m e n are. This analysis contr ibutes additional measures of EEOC enforcement , a current analysis o f the different effects for black and white women , and a solution to the p rob lem o f endogenei ty between wages and charges.

N O T E S

1. Teresa Amott and Julie Matthaei. 1991. Race, Gender and Work: A Multicultural Economic History of Women in the United States (Boston: South End Press).

2. Barbara J. Robles. 1997l An economic profile of women in the United States, in Women and Work: Exploring Race, Ethnicity, and Class, ed. Elizabeth Higginbotham and Mary Romero., Women and Work: A Research and Policy Series (Thousand Oaks, CA: Sage Publications).

3.42 U.S.C. 2000e. 4. Other equal employment opportunity laws and executive orders include the

Civil Rights Act of 1991, other provisions of the Civil Rights Act of 1964 (which includes Title VI, Title IX as amended and Title XI), Title I of the Civil Rights Act of 1968, the Attorney's Fees Award Act of 1976, Title IX of the Education Amend- ments of 1972, the Age Discrimination in Employment Act of 1967, the Age Dis- crimination Act of 1975, the Equal Pay Act of 1963 the Rehabilitation Act of 1973, the Americans with Disabilities Act of 1990, the Vietnam Era Veterans' Readjustment Assistance Act of 1974, the Immigration Reform and Control Act of 1986, the Family and Medical Leave Act of 1993, and the Religious Freedom Restoration Act of 1993.

5. The 1971 landmark decision in Griggs v. Duke Power Co. (401 U.S. 424, 1971) held that the use of facially neutral criteria in hiring, promoting, or classifying individuals that had a disparate impact on a protected class was prima facie unlawful.

6. U.S.Equal Employment Opportunity Commission. Statement by EEOC Chair- man Gilbert Casellas on proposed settlement agreement with Texaco. Press Release. 1-3-1997. http://www.eeoc.gov/press/1-3-97.html, 1

7. Anne Reifenberg, 1997. Texaco settlement in racial-bias case endorsed by judge, Wall Street Journal, 25,1.

8. See Francine Blau, Marianne Ferber, and Anne Winkler, The Economics of Men, Women and Work (Englewood Cliffs, NJ: Prentice-Hall, 1998) for a descrip- tion of wage and employment outcomes as well as descriptions of different forms of discrimination.

9. See Arthur H. Goldsmith, William A. Darity Jr., and Jonathan R. Veum. Race, cognitive skills, psychological capital, and wages, Review of Black Political Economy (1998): 9-21 and Rhonda M. Williams and William E. Spriggs, "How Does It Feel to Be Free?: Reflections on Black-White Economic Inequality in the Era of 'Color Blind' Law.," Review of Black Political Economy (1999): 9-21 for overviews of the literature on wage discrimination against Blacks.


10. Charles Brown, The federal attack on labor market discrimination: the mouse that roared? in Research in Labor Economics Vol. 5, ed. Ronald G. Ehrenberg. (Greenwich, CT: JAI Press, 1982). and John J. I, Donohue and James Heckman, Continuous vs. episodic change: the impact of civil rights policy on the economic status of nlacks, Journal of Economic Literature 29, no. 4 (1991): 1603-1643; Rich- ard B. Freeman, Black economic progress after 1964: who has gained and why?, in Studies in Labor Markets, ed. Sherwin Rosen. (Chicago: University of Chicago Press, 1981), 247-294; and Jonathan S. Leonard, The impact of affirmative action tegulation and equal employment law on black employment, Journal of Economic Perspectives 4, no. 4 (1990): 47-63.

11. Beller, Andrea H. The economics of enforcement of Title VII of the Civil Rights Act of 1964. Institute for Research on Poverty, University of Wisconsin. Discussion Paper 313-75. 1975. Richard Butler and James Heckman, The government's impact on the labor market dtatus of black americans, in Equal Rights and Industrial Relations, ed. L. J. Housman. (Madison, WI: Industrial Relations Research Association, 1977), 235-281 also showed negative impacts however, this paper contained keypunch errors that were corrected in Freeman's Black economic progress after 1964: who has gained and why?

12. Andrea H. Beller, EEO laws and the earnings of women, Proceedings for the 29th Annual Winter Meeting (1977): 190-198; Andrea H. Belier, The impact of equal employment epportunity laws on the male-female earnings differential, in Women in the Labor Market, ed. Cynthia B. Lloyd, Emily S. Andrews, and Curtis L. Gilroy. (New York: Columbia University Press, 1979); Andrea H. Beller, Occupational segregation by sex: determinants and changes, Journal of Human Resources I7, no. 3 (1982): 371-392; Richard B. Freeman, Changes in the labor market for black Americans, 1948-1972, Brookings Papers on Economic Activity l (1973): 67-120; Jonathan S. Leonard, Employment and occupational advance under affirmative action, Review of Economics and Statistics 66, no. 3 (1984): 377-385; Jonathan S. Leonard, The impact of affirmative action on employment, Journal of Labor Eco- nomics 2, no. 4 (1984): 439-463; Jonathan S. Leonard, Women and affirmative action, Journal of Economic Perspectives 3, no. 1 (1989): 61-75; Paul Osterman, Affirmative action and opportunity: a study of female quite rates, Review of Eco- nomics and Statistics 64, no. 4 (1982): 604-612; and Noel D. Uri and J. Wilson Mixon, Impact of the equal employment opportunity and affirmative action programs on the Employment of Women in the US, Labour 5, no. 2 (1991): 89-104.

13. Jonathan S. Leonard, Wage disparities and affirmative action in the 1980s, American Economic Review 86, no. 2 (1996): 5-289; James Heckman and Kenneth Wolpin, Does the contract compliance program work? An analysis of Chicago data, Industrial and Labor Relations Review 29, no. 4 (1976) and Uri and Mixon. Uri and Mixon found improvements in the relative employment of women, some of which was lost in the 1980s. Leonard saw no effects in the 1980s for anyone. The studies considering the t980s showed that these programs had little or no impact during that decade. The 1980s was a decade of substantially declining concern by the Reagan Administration for equal employment issues. The results above may indicate that the lack of commitment to these policies may be the cause of the lack of evidence supporting these programs.

14. Belier, EEO laws and the earnings of women. 15. U.S.General Accounting Office. Equal employment opportunity: EEOC and

state agencies did not fully investigate discrimination charges. 11 October1988. GAO/ HRD-89-11.

16. U.S.Congress.House.Committee on Education and Labor: Subcommittee on Select Education and Civil Rights. Oversight hearing on the Equal Employment

Wilhelm 51

Opportunity Commission: hearing before the Subcommittee on Select Education and Civil Rights of the committee on Education and Labor. 103rd Congress, First Ses- sion. 1993, 7.

17. M. V. Lee Badgett and Heidi I. Hartmann, The effectiveness of equal employment epportunity policies, in Economic Perspectives on Affirmative Action, ed. Mar- garet C. Simms. (Washington D. C.: Joint Center for Political and Economic Studies, Inc., 1995), 55-91.

18. Gary Becker, The Economics of Discrimination (Chicago: The University of Chicago Press, 1975).

19. Lauren Edelman, Legal ambiguity and symbolic structures: organizational mediation of civil rights law," American Journal of Sociology 97, no. 6 (1992): 1531-1576.

20. Edelman. 21. Leonard, The impact of affirmative action regulation and equal employment

law on black employment. 22. Williams and Spriggs, 10, 23. James J. Heckman, Sample selection bias as a specification error with an

application to the estimation of labor supply functions, in Female Labor Supply: Theory and Estimation, ed. James P. Smith. (Princeton: Princeton University Press, 1980).

24. Average hourly wages in terms of 1982 dollars were $7.69 in 1988 and $7.43 in 1996, indicating that wages were falling over this period. Bureau of Labor Statis- tics. Not seasonally adjusted, total private, average hourly earnings, 1982 dollars. Extracted 21 November 2002.

25. Leonard, The impact of affirmative action on employment. 26. Heckman. 27. Butler & Heckman; Freeman, Changes in the labor market for black Americans. 28. Belier, EEO laws and the earnings of women. 29. Andrea H. Belier, The economics of enforcement of an anti-discrimination

law: Title VII of the Civil Rights Act of 1964," Journal of Law and Economics 21, no. 2 (1978): 359-380.

30. Leonard, The impact of affirmative action on employment. 31. Steven Shulman, Discrimination, human capital, and black-white unemploy-

ment: evidence from cities, Journal of Human Resources 22, no. 3 (1987): 361-376. 32. Shulman. 33. Leonard "Wage disparities and affirmative action in the 1980s. 34. While two of the coefficients are significant at the 10% level, this does not

seem sufficient to suppose a correlation with a sample size of 20946. 35. Belier, EEO laws and the earnings of women. 36. U.S.Equal Employment Opportunity Commission. National Database. (2000).

Extracted 17 November 2000. 37. Beller, EEO laws and the earnings of women. 38. Beller, EEO laws and the earnings of women

the impact of equal employment opportunity commission enforcement on the wages of black and white...

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