gender role ideology and the gender based differences in earnings

Gender Role Ideology and the Gender BasedDifferences in Earnings

Juanita M. FirestoneRichard J. HarrisLinda C. Lambert

The University of Texas at San Antonio

ABSTRACT: Much of the research on gender differences in occupational earnings stillfocuses on human capital and the structure of the labor market. However, these vari-ables rarely explain even half of the gender gap in earnings. Most research has exam-ined the impact of gender role ideology as it impacts occupational choice, which indi-rectly can impact earnings. Using data from the National Opinion Research CenterGeneral Social Surveys, this research focuses on the relationship between attitudesabout gender roles and two variables: (a) earnings, and (b) occupational positions heldby women and men. Findings show that traditional gender-role ideology contributes tolower observed earnings for both males and females, independent of the influences ofhuman capital characteristics, occupational context, and ascribed characteristics. Re-sults support socialization as a partial explanation for the gender-based earnings dif-ferences and suggest that, to the extent that economic rewards are used to assess thevalue of gender role expectations, traditional gender role attitudes might continue tochange and lead to relatively equal earnings among women and men.

KEY WORDS: earnings, gender, gender role, socialization.

Introduction

Researchers have put considerable effort into the analysis of earn-ings or wage determination in recent years. Although knowledge of

Juanita M. Firestone is Associate Professor of Sociology, Division of Social and PolicySciences, The University of Texas at San Antonio, TX 78249. Her research interestsinclude gender issues, stratification, and quantitative methods.

Richard J. Harris is Associate Professor of Sociology, Division of Social and PolicySciences, The University of Texas at San Antonio. His research interests focus on de-mography, quantitative methods, and stratification.

Linda C. Lambert has just completed her MS in Sociology, Division of Social andPolicy Sciences, The University of Texas at San Antonio, Her research interests focuson stratification, family, and quantitative methods.

Please direct communications to the first author by e-mail at: [email protected].

Journal of Family and Economic Issues, Vol. 20(2), Summer 1999© 1999 Human Sciences Press, Inc. 191

Journal of Family and Economic Issues

this area has improved due to these efforts, a sizable difference inwages between men and women exists that cannot be explained bydifferences in human capital; workers' commitment; market, job andindustry structures; or any other measured attribute of individualworkers that has been studied (see for example: Duncan, 1996; Filer,1883; Hersch, 1991; Kilbourne & England, 1996; Killingsworth, 1987;Mallan, 1982; Parcel & Mueller, 1983; Rosenfeld & Kalleberg, 1990;Sorensen, 1989; Thacker, 1995; Ward & Mueller, 1985).

This research focuses on factors related to socialization and genderrole attitudes that may influence earnings and occupational choicesmade by women and men. Most research has examined the impact ofgender role ideology on occupational choice, which then can impactearnings. For example, some researchers suggest that women choosejobs that require less time, energy, and emotional input in order toconserve these resources for dealing with family responsibilities (e.g.,Becker, 1985). Similarly, gender role attitudes conceivably could af-fect performance and wage bargaining techniques. Some literaturesuggests that the stereotypically female characteristic of nurturanceis valued less in the labor market than the stereotypically male char-acteristic of aggressiveness (Kilbourne & England, 1996). Further-more, women who have internalized traditional beliefs about howwomen should act may be less likely to behave assertively when theydo not receive a raise or promotion (Betz & Fitzgerald, 1987). Bothsituations suggest that women with traditional gender role orienta-tions would earn less money. Because traditional male characteristicshave been rewarded in the work place, gender role attitudes may notbe an important determinant of men's earnings.

Literature Review

Human Capital Approach

There are many possible reasons why individuals are paid at differ-ent rates. These reasons include differences in the quality and skill ofworkers, the distribution of workers across industries and occupa-tions, the degree of pay discrimination, and the relative demand andsupply of labor. Human capital theory, which derives from the neo-classical economic theory of wages, argues that individuals havehigher earnings if they make investments in themselves that increasetheir value to employers. Pay differences between individuals can be

192

Juanita M. Firestone, Richard J. Harris, and Linda C. Lambert

explained by human capital, which is the totality of achieved capaci-ties a person possesses (Becker, 1971; Mincer, 1974). One's humancapital can depreciate through obsolescence or non-use, such as whena homemaker is out of the labor force. Researchers using the humancapital theory approach assume that differences in productivity de-rive from differences in human capital such as education and train-ing, work experience, continuity of work history, effort, commitment,health, etc., all of which can be measured more directly than produc-tivity itself. According to this perspective, women are paid less thanmen because they invest less in terms of schooling, work experience,and other elements of human capital and therefore are less produc-tive than men.

Neoclassical economists assume that most individuals act in ratio-nal ways and, as a result, select the means they believe will lead tothe most desirable outcome (Killingsworth, 1987). In addition, theirown preferences influence decisions regarding which means to utilizein seeking their goals. "Tastes determine how much utility is providedby different combinations of leisure, honor, types of work, children,etc." (England & McCreary, 1987a). Using this perspective, econo-mists argue that women may place more importance on the non-pecu-niary satisfaction of work and, in essence, trade off earnings for thosesatisfactions. One variant of the argument views gender-differenti-ated psychological dispositions as kinds of human capital and showsthat these differences explain some of the sex difference in earnings(Filer, 1983). Using this logic, females tend to invest in the kinds ofhuman capital such as social or family relationships that have rela-tively low monetary rewards. Thus, women may view jobs that re-quire less physical, cognitive, or emotional effort as necessary formeeting familial responsibilities even if those jobs receive relativelylow wages (Becker, 1985). However, Bielby and Bielby's (1985) studyshowed that the evidence does not support this hypothesis. Womenreported slightly more effort than men did, with an increase in thedifference when human capital and household responsibilities werecontrolled. These findings, coupled with research from equity theorysuggesting that women tend to underestimate their performance, pro-vide evidence against Becker's hypothesis. Much of the research ongender differences in occupational earnings still focuses on humancapital and the structure of the labor market. However, these vari-ables rarely explain even half of the gender gap in earnings. Duncan(1996) suggests that educational attainment is important for earningsat the beginning of a career, especially for females. However, as expe-

193


rience in the labor market increases, education becomes increasinglyimportant for male earnings, while the impact of education for femaleearnings remains steady. This suggests that work experience is moreimportant for females than for males and education is more influen-tial for males than for females (see also, Mortimer & Lorence, 1979).

Darity, Guilkey, and Winfrey (1996), in a study designed to assessdiscrimination or inexplicable differences in earnings for minorities,found evidence of differential treatment by race and ethnicity forAmerican males but no such evidence for females. Their results placedoubt on three bases of oppression (i.e., gender, race, and class),which are suggested by some researchers for female minorities in theearnings arena. Several researchers have concluded that racial andethnic differentials can be explained by cultural variations, which arehuman capital measures (e.g., Sowell, 1981; Chaswick, 1983, 1985).However, Darity, Guilkey, and Winfrey (1996) decomposed the Blackand non-Black population along culturally homogeneous lines. Theirconclusion is that "culture as human capital does not provide an ade-quate explanation of intergroup variations in wages (Darity, Guilkey,& Winfrey, 1996)." This suggests that race is what matters, not differ-ences in cultural values (also see Woodbury, 1993).

Gender Roles and Occupational Context

Strong forces of socialization and sex-role norms teach children atvery young ages that certain jobs are identified with either men orwomen. Although forces of socialization of gender role stereotypes areundergoing rapid change, the pressures on young females to choosecareers or jobs traditionally appropriate for women remain strong(England & McCreary, 1987b). Thus, occupational segregation re-mains important. In 1993-1994, 98% of all secretaries, stenogra-phers, and typists were women (U.S. Bureau of the Census, 1994),although levels of segregation had declined during the 1970s and1980s.

Recent research by sociologists and economists emphasizes the im-portance of work structure and roles on earnings. These include charac-teristics of an individual's occupation such as level of skill, industry,organization, position of authority, control over working conditions,and unionization. Kalleberg and Berg (1987) suggest these charac-teristics are interrelated and should be considered in studies of eco-nomic inequality. Research shows that men and women differ inmany of these characteristics. For example, women are more likely

194


than men to be in clerical occupations and in service industries.Women in the U.S. are less likely to belong to labor unions (Feldberg,1987), and women are less likely than men to have jobs with author-ity (Duncan & Corcoran, 1984; Ward & Mueller, 1985).

However, even within broad occupational categories, women are likelyto hold different jobs than men, and, when identified with the sameCensus occupational code, women are found in lower paying jobs thanare men. Reskin and Roos (1990) suggest that segregation in mixed-sexoccupations ensures that women rarely earn as much as their malecounterparts. England (1992) provides evidence that occupations with ahigh percentage of females depress wages for both genders.

Some types of occupational skills required in a job may net lowerreturns due to gender discrimination. For example, women are foundmore often in jobs involving nurturant social skills than are men, andthese jobs have lower returns than jobs requiring other types of socialskills such as authority (Steinberg, 1990). England (1992) found thatoccupations involving authority had a positive impact on earnings,with men earning more in these positions than women. Jobs requir-ing nurturance skills had a negative effect on earnings, with womenearning more in these positions than men.

England (1992) suggests that lifelong socialization leads men andwomen to find different jobs interesting, respectable, of value, or con-sistent with gendered identities. Preferences for certain kinds of workentail preferences for exercising certain kinds of skills. It is possiblethat jobs affect values as much as values affect job choice. Thus,values and jobs may be related reciprocally. Insofar as gender-specificsocialization orients men and women toward gender-differentiatedjobs and skills and female-dominated jobs pay less than male-domi-nated jobs, values may play a part in the gender gap in earnings.

Structural positions, such as paid jobs or other roles, also create afeedback effect by encouraging the worker to have characteristics re-quired for the role, even if this is not in the individual's best interest(Kohn & Schooler, 1978). If women are disproportionately assigned tojobs requiring traditionally feminine skills and qualities (e.g. typingand nurturance), this will tend to increase gender differences in skillsand qualities that existed before such assignments. This practicehelps perpetuate future gender differences in types of jobs workedand subsequent earnings. If this view is accurate, individuals infemale-dominated occupations, especially those requiring nurturantskills, would be expected to earn less than those in male-dominatedoccupations.

195


Family Demographics

The literature provides mixed findings on the effect of marital sta-tus on earnings. Duncan's 1996 study shows that being married has apositive effect on earnings for Black and White males and Black fe-males and a negative effect on earnings for White females. Childrenever born had a negative effect on females' earnings and no effect onmales' earnings. Sorenson (1989) found differential effects for malesand females for presence of children in the home under age five, witha significant positive influence for males and a significant negativeinfluence for females. Laws (1989) found that marriage and childrenaffect women's work and career opportunities more than work affectsfamilies.

Attitudes, Values and Earnings

Values comprise "an individual or collective conception of thatwhich is desirable," and an attitude is defined as "a predisposition torespond to a focal object. . . these predispositions, or sets, are learnedthrough experience . . . and by far the most important component [ofattitudes] is the evaluative dimension" (Lachman, 1991). Thus, workvalues invoke a collective conception about desirable qualities andgender role attitudes comprise aggregated individual evaluative re-sponses to ideas about traditional roles for men and women.

Some researchers have addressed the influence of work values andattitudes on earnings indirectly. For example, Marini (1978) and Mar-ini and Brinton (1984) examined the effects of the aspirations andexpectations of high school students on their subsequent occupationalattainment. Marini, Fan, Finley, & Beutel's (1996) recent research onthe influence of job values (i.e., what people want in a job) and reli-gious values (e.g., the Protestant Ethic) of youths indicates that thesevalues have a stronger influence on job choice than other backgroundvariables. This is of substantive importance because one's occupa-tional choice is particularly important to subsequent earnings out-comes.

Marini and her colleagues (1978, 1984, 1996) found that, althoughboth males and females give importance to the intrinsic, altruisticand social rewards of work, young women value these attributes morehighly than young men. The effect of gender on earnings through jobvalues was more important than the effect of other background vari-ables included in one study, such as race, parents' education, mothers'

196


employment, community of origin, and religion (Marini et al., 1996).However, females and males planning to enter the same occupationare similar in the values they attach to a job (Marini et al., 1996).Furthermore, contrary to suggestions that females choose jobs thatrequire less dedication and that females invest less effort in a job dueto adult role responsibilities, Marini et al. (1996) found that malesplace more importance on the leisure time a job affords than do fe-males.

Other aspects of value differences also may affect actual job perfor-mance or commitment, which can influence earnings outcomes. Forexample, Marini and her associates (1996) found that females place ahigher importance on the social aspects of a job and on obtaining a jobthat matches their abilities. If females' jobs match their abilities, per-formance on the job should not be a problem. However obtaining a jobthat meets the social needs they have been taught to value without aconcurrent focus on matching their abilities could lead to lower per-formance of job duties, which would impact wages negatively.

Thacker (1995) provides a direct test of the influence of job charac-teristics and preferences on salary. Her research suggests that prefer-ences for independence and personal interaction are both positivelyrelated to salary. In separate regression analyses for males and fe-males, personal interaction preferences have a significant positive in-fluence on salaries of men, and preferences for upward mobility havea significant negative influence on salaries of females. However,Thacker's research is limited to a single university, which was a for-mer all-male, all-military institution. Additionally, she chose to omitfrom the analyses gender-dominant job positions. This severely limitsthe generalizability of her findings. Hersch (1991), using a non-ran-dom sample, tested the impact of work conditions (i.e., riskiness ofjob, extent of responsibilities, training requirements, mental andphysical qualifications) and found that they had little influence on thegender gap in wages. Kilbourne et al. (1994) found that, in contrast tothe predictions of the neoclassical model, onerous physical conditionsdid not have a consistently positive impact on wages, nor did theyexplain much of the gender wage gap.

It may be the case that if a woman thinks she should be at home,she is less likely to be committed to the work place. Furthermore, if amale who believes a woman's place is in the home decides a woman'spromotional opportunities and salary, this also can impact her earn-ings negatively. Gender role socialization has been used by researcherstrying to explain occupational segregation by race and sex (e.g., En-

197


gland & McCreary, 1987b). However, gender role ideology has notbeen utilized in attempts to explain the gender gap in earnings di-rectly, although Mallan (1982) suggested the inclusion of socializa-tion, gender role stereotyping, and role differentiation of women aspossible constraints on women's occupational choices that lead to lowpaying positions (see also Betz & Fitzgerald, 1987).

"Gender role attitudes are generally conceived of as opinions andbeliefs about the ways that family and work roles do and should differbased on sex" (Harris & Firestone, 1998). These attitudes typicallyrun along a continuum from traditional to nontraditional. Traditionalgender roles are those which reinforce or conform to expected differ-ences in roles for men and women.

The socialization process, which thus far has failed to adjust tochanging gender roles, puts great pressure on women in the paid la-bor force. Data clearly show that women, employed or not, spendmuch greater portions of their time on homemaking and child-rearingresponsibilities than do men (Hersch, 1991; Shelton, 1992). Younggirls still learn domestic skills at a younger age and do more house-hold chores than do young boys (Zill & Rogers, 1988). Additionally,the institutional structure of work has failed to accommodate work-family conflicts, which influences the career development of profes-sional women because family responsibilities are disproportionatelycarried by females.

Females with traditional gender-role values may be less authori-tarian and aggressive in the job market than men. The reverse wouldbe true for males with a traditional gender-role ideology. These twoextremes likely would engage in opposite methods of promotion at-tainment, and the outcomes may be different. Indeed, the processprobably is compounded when the person responsible for making deci-sions about wages and promotions has stereotyped views about theappropriate roles of women (Facteau & Dobbins, 1996). However,changes in gender relations in America during the 1990s may meanthat holding traditional gender role ideologies can be a detriment tomen's careers or chances for promotion. Employers may view thesemen as "lacking in openness to diversity" or as open invitations todiscrimination lawsuits. Thus, both men and women would receivenegative returns for holding traditional views about gender roles.

This research attempts to answer the following questions: (a) dogender role attitudes in particular and socialization in general influ-ence earnings independent of differences in human capital, demo-graphic characteristics, and occupational context? and (b) does the

198


inclusion of a measure of gender role ideology help to explain a largerproportion of the gender gap in earnings?

Methods and Sample

Sample

The National Opinion Research Center's General Social Surveysprovide a unique opportunity to investigate attitudinal effects onearnings. "Each survey is an independently drawn sample of English-speaking persons 18 years of age or over, living in non-institutionalarrangements within the United States" (Davis & Smith, 1994: 1),based upon " . . . a stratified, multistage area probability sample ofclusters of households . . ." (Davis & Smith, 1994: 785). In contrast tomost other data sets (e.g., Current Population Surveys, Panel Studyof Income Dynamics), these surveys include a useable measure ofearnings and a large variety of attitudinal variables which can beused to form a good index measuring gender role ideology. This makesit one of the only data sets to allow analysis of the effects of genderrole attitudes on earnings.1 Years for which all data in our analysisare available include 1991, 1993, and 1994. All three survey yearswere combined to provide a sufficient sample size for generalizability.The resulting sample includes 1081 male and 1175 female respon-dents in the labor force.

Variable Construction

Data for the dependent variable, earnings, were collected in catego-ries in the General Social Surveys (GSS). The data were transformedby assigning the midpoint value of each category.2 Earnings are ad-justed further to relative purchasing power for each year using theConsumer Price Index with a base year of 1986. An increase in un-earned income is thought to produce a decrease in individual earn-ings by reducing the time an individual devotes to income-producinglabor (Bryant, 1991). Thus, a control for other family income is in-cluded and is measured as the difference between reported family in-come and respondent's earnings.

Human capital variables include education, age (as a proxy for laborforce experience), and job structure (e.g., hours worked, occupationalprestige). Education is measured in years of completed schooling.

199


There are no variables in the GSS to measure labor force experiencedirectly. Researchers in economics often use a proxy that measurespotential experience. Potential experience is constructed by takingthe respondent's age, subtracting years of education, and then sub-tracting six, the age most people in the United States start firstgrade. Potential experience is not the same as actual experience formany people. In previous work, this calculation has been shown to bea good experience proxy for males. However, potential experience gen-erally overestimates the actual experience for women. For example,Sorenson (1989) found that men's work experience is almost twicethat of women's. However, a comprehensive search for a set of demo-graphic predictors for labor force experience did not yield a betterproxy than age.3 Because age is highly correlated with income for bothmales and females, age is used as an experience proxy so the equa-tions will be comparable. Evidence also suggests that age has a cur-vilinear relationship with earnings, peaking around age 50 and thendeclining with increasing age. The age variable is squared, and bothage and age-squared are included in the model to capture this rela-tionship. An interaction term of education and age also is included tocapture the potential compounding effects of seniority and high edu-cational credentials on earnings.4

Job structure variables include hours worked and occupationalprestige. Hours worked refers to the number of hours the respondentworked the week prior to the interview. For respondents who werenot at work that week due to temporary illness, vacation, or strike,hours worked refers to the number of hours they usually work in aweek. A series of dummy variables was created. These variables rep-resent 21 to 34, 35 to 40, 41 to 45, 46 to 51, and 52 or more hoursworked per week. The omitted category is 20 hours or less. Occupa-tional prestige measures the social standing of occupations from lowto high (See Davis & Smith, 1996: 1086).

Because earnings refer to the prior year and hours worked refers tothe current year, this research assumes that respondents, on average,are working the same number of hours last week as they did for anaverage week last year. Furthermore, the hours worked question asksabout all jobs, and the earnings question asks about the primary job.Thus, earnings will be underestimated somewhat for respondentswho work more than one job.5

Occupational context refers to occupations that are male and fe-male-dominated, those requiring nurturant skills, and those requir-ing authority skills. Occupation is receded into dummy variables rep-

200


resenting those that require nurturant skills and those that requireauthoritative skills, with all others acting as the reference group. En-gland's (1992) classification codes are used to develop these dummyvariables (see Appendix A).

Demographic and family variables include: race and ethnicity, sex,marital status, number of children, geographic region, and urban res-idence. Region is recoded as a dichotomous variable measuring thesouthern region versus non-southern regions. This control is neces-sary because wage structures and industries differ by region. Urbanresidence is included to control for differing wage structures and em-ployment opportunities in rural and urban areas. Rural is defined asliving in a county with no cities with 10,000 or more population.

The race and ethnicity variables are combined, and dummy vari-ables are constructed to measure White, Black, and Hispanic eth-nicity. Marital status is recoded into dummy variables representingmarried or separated; never married; and divorced or widowed indi-viduals. Number of children refers to number of children ever born.All variables are coded so that higher scores indicate more of thenamed characteristic.

Finally, gender role ideology is measured with an eight-item indexfocusing on gender role issues with respect to employment and con-flicts involving one's job family. Cronbach's alpha for this index is .79.The index includes responses to statements related to beliefs aboutwomen's roles in paid labor, in the political sphere, in the household,and in childcare (See Harris & Firestone, 1998). Table 1 shows theitems used to construct this index along with item-to-index correla-tions and reliability coefficients. Higher scores on this index indicatea more traditional gender role ideology.

Table 2 presents descriptive statistics of the sample separately formales and females. In this sample, 13% of females and 9% of malesare Black. Just over half of the females were married or separated,with an average of 1.9 children. Just under two-thirds (64%) of themales were married or separated, with an average of 1.7 children.Ninety percent of both males and females lived in urban areas; 34%resided in the southern region. In constant 1986 dollars, the averagefemale income is $14,828 with an average occupational prestige rank-ing of 44 compared to an average income of $23,765 for males with acomparable prestige average. These men and women have equallevels of education at 13.7 years. The average age of both males andfemales is 42 years. Thirty percent of females were employed in occu-pations requiring nurturant skills compared to 8% of males. Eleven-

201

202 Journal of Family and Economic Issues

percent of females and 18% of males were in occupations requiringauthority skills. Only 11% of females were employed in male-domi-nated occupations, and 41% were employed in female-dominated oc-cupations. A majority of males (54%) worked in male-dominated occu-pations, and only 5% of males worked in female-dominated ones.Sixty-seven percent of women and 81% of men worked more than 35hours the week prior to the interview, and over 43% of women and32% of men worked between 35 and 40 hours the week prior to theinterview. The majority of males were working more than 40 hoursper week. Males are more traditional in their gender role attitudes(score = 1.91) than are their female counterparts (score = 1.31).

TABLE 1

Questions Used in the Gender Role Ideology Index, with Item-to-indexCorrelations and Reliability Coefficients

Do you agree or disagree with this statement?Women should take care of running theirhomes and leave running the country up tomen.

Do you approve or disapprove of a marriedwoman earning money in business or industryif she has a husband capable of supporting her?

If your party nominated a woman for President,would you vote for her if she were qualified forthe job?

Tell me if you agree or disagree with thisstatement: Most men are better suitedemotionally for politics than are most women.

A working mother can establish just as warmand secure a relationship with her children asa mother who does not work.

It is more important for a wife to help herhusband's career than to have one herself.

A presschool child is likely to suffer if his or hermother works.

It is much better for everyone involved if the manis the achiever outside the home and thewoman takes care of the home and family.

Cronbach's Alpha = 0.79

FEHOME: Agree = 1

FEWORK:No = l

FEPRES:No=l

FEPOL: Agree = 1

FECHLD: Disagree = 1

FEHELP: Agree = 1

FEPRESCH: Agree = 1

FEFAM: Agree = 1

0.73

0.49

0.58

0.64

0.64

0.70

0.66

0.77

Number of Cases = 11,371(based on all years 1985-1994)

Juanita M. Firestone, Richard J. Harris, and Linda C. Lambert 203

TABLE 2

Means and Standard Deviations of Key Variables

DemographicBlackHispanicChildrenMarried/separatedSingleUrbanSouth

Income ($)Unearned income ($)

Human capitalPrestige (score)Education (years)Age (years)

Occupational contextNurturantAuthorityMale-dominatedFemale-dominated

Hours worked per weekHRS2134HRS3540HRS4145HRS4651HRS52UP

Gender role indexN

Females

Mean

.13

.041.89.59.15.90.34

14828.0913518.77

44.1013.7142.26

.30

.11

.11

.41

.12

.43

.06

.08

.10

1.301175

Std. Dev.

.33

.201.55.49.36.30.47

10188.6714051.16

13.412.64

11.81

.46

.32

.32

.49

.32

.50

.24

.27

.30

1.65

Males

Mean

.09

.041.66.64.20.90.34

23765.127028.19

45.1013.7241.91

.08

.18

.54

.05

.06

.32

.09

.15

.25

1.911081

Std. Dev.

.29

.201.56.48.40.30.47

14818.859349.86

13.462.97

11.83

.28

.39

.50

.21

.24

.47

.29

.36

.43

1.83

Source: NORC General Social Surveys, 1991, 1993, & 1994.Note: all means for dummy variables (e.g., Black, nurturant occupations) represent

the proportion with the respective attribute.

Analytical Strategy

Parcel and Mueller (1983) suggest that researchers should considerinteraction effects of sex with race, age, and marital status. Otherresearchers have found interaction effects of gender with children,prestige, hours, and race or ethnicity. Rather than include a multi-


tude of interaction terms that tend to complicate interpretation, sepa-rate regressions were completed for males and females, and t-testswere used to compare the resulting slopes to assess whether differ-ences were statistically significant.

The regression analysis on earnings was entered hierarchically toallow for assessment of the influence of each additional group of vari-ables. By entering the variables in staged groups, the change in re-gression results in response to each new model specification can bebetter examined. Race-ethnicity, urban residence, region, age, educa-tion, occupational prestige, hours worked, marital status, children,male- and female-dominated occupation dummy variables, and dummyvariables for authority and nurturant skills were entered in the firststage (Model I). In the second model, gender role ideology is included.Interaction terms were entered in the final model. Transformations,such as age-squared, enter the model along with the original variable.

Findings

In bivariate associations, earnings are positively related to pres-tige; education; the dummy categories for 41 to 45, 46 to 51, and 52and over hours worked per week; living in an urban area for bothmales and females; age; age-squared; and the age and education in-teraction term. In addition, the dummy category of 35 to 40 hoursworked per week is positively related to earnings for women. How-ever, for men additional variables hold positive relationships withearnings: having never been married, being married, and the interac-tion of married with children. For women, the interaction of beingmarried with children in related negatively to earnings. Earnings arenegatively associated with female-dominated occupations, those occu-pations requiring nurturant skills, southern residence, being Black orHispanic, and relatively traditional gender role ideology for bothsexes.

Table 3 provides the results of a three-stage hierarchical model,which used ordinary least squares regression to predict earnings formales and females. Several predictors are notably significant for thefemale equation and are not significant for males. Education and au-thority-skilled jobs are significantly and positively associated with fe-males' earnings, but they do not reach statistical significance for menin the final model. Additionally, the interactive term for educationand age has a significant positive impact on men's earnings, but no

204


impact on the earnings of women. Women receive strong, positive re-turns to earnings for increasing years of education, but the relation-ship becomes small and non-significant for men after introducing theeducation-age interaction term. Occupations requiring authority skillshave a positive effect on both female and male earnings, and the ef-fect is negative for females and males in nurturant occupations. Thisgender difference is statistically significant. Females in male-domi-nated occupations tend to earn more than those in other occupations,and males in male-dominated occupations earn less. This impact issignificant for both men and women, and the difference by gender issignificant. Both males and females in female-dominated occupationsearn less. The negative impact of working in a female-dominated oc-cupation is far greater for men than for women. Statistically signifi-cant differences between male and female slopes occur for severalpredictor variables (see t-values, Table 3). Other family income nega-tively impacts both men's and women's earnings but has a signifi-cantly stronger relationship with the earnings of men. The strongerimpact for men than for women is consistent with men with middleand lower incomes being more likely to have spouses in the laborforce than men with high incomes. This is supported by separate bi-variate analysis comparing earnings levels within categories of spou-sal employment. In comparing the adjusted multiple correlation coef-ficient squared (Adj. R2), the model explains more of the variance infemale earnings (45.2%) than it does for male earnings (43.8%).

Finally, traditional gender role ideology is related negatively toearnings for both males and females, with the impact being slightlylarger for men than for women. Gender role ideology is a statisticallysignificant addition to the explanatory power of the overall models.Men and women with more traditional gender-role ideologies tend tohave lower earnings. Gender role ideology significantly increases theR2 for men, but the increase is not significant for women. Because theindex is significant in the overall model but does not increasethe amount of variance explained, it is possible that, for women, gen-der role ideology captures some of the variance in earnings previouslyattributed to other variables in Model I. The addition of the two inter-active terms (i.e., marriage and children, education and age) providesa significant contribution to the model for women but not for men.

After controlling for the two interaction terms (i.e., education andage; married and children), the impact of education on the earnings ofmen becomes negligible and non-significant with the influence of edu-cation being captured completely by the education and age interaction

208


term. Education remains moderate and significant for women. Thesedifferences are not due to multicollinearity because the correlations ofthe interaction term with age are about the same for both men andwomen.

Alternatively, the differences in earnings attributed to age, whichis a proxy for work experience, are moderate and statistically signifi-cant for both men and women, although impact decreases for menwhen the interaction terms for education and age are added to themodel. Because the average ages of men and women in this sampleare equal, the interaction of education and age of men overpowers theimpact of education alone, with the greatest gains possibly accruingto highly educated men in their forties and fifties. The combination ofeducation and age, which is a proxy for experience, does not have thesame positive relationship for women once the other variables arecontrolled. Thus, highly educated women may not reap the same ben-efit from experience as do men. Having children produces non-signifi-cant associations with earnings for both men and women; the positiverelationship for men (b = $458) is larger than the positive associationfor women (b = $184). This may reflect recent economic exigencies inwhich both parents, regardless of the presence of children, are likelyto be employed outside the home.

Conclusions

The primary focus of this research was to determine the impact ofsocialization, measured by gender role attitudes, on earnings inde-pendent of differences in human capital, demographic characteristics,and occupational context. Occupational context is an important pre-dictor of earnings for men and women. Being employed in a male-dominated occupation has a negative impact on earnings for men butis positive for women. A large negative impact on earnings for bothmen and women occurs for those individuals employed in female-dom-inated occupations, and the impact is more than twice as strong formen. The same is true for individuals employed in those occupationsrequiring nurturant skills. The differences between men and womenare not statistically significant in either case (see Table 3). Being em-ployed in an occupation requiring authority skills has a significant,positive impact on earnings for women and for men. These findingsprovide strong support for the socialization explanations of gender-based occupational wage differences (England & McCreary, 1978b;

209


Moen, 1992; Shelton, 1992). Bias against women, which can be re-flected in wages, may be maximized when people with traditional at-titudes about gender roles evaluate individuals based upon tradi-tional gender-role expectations (Basow, 1992: 278). Thus, both womenand men in occupations requiring nurturant skills, which are viewedas traditionally female, receive low returns to labor force experience,independent of human capital and demographic characteristics. Fur-thermore, the relationship depresses men's earnings twice as much aswomen's. Women who enter male-dominated occupations and occupa-tions requiring authority skills are able to maximize their wage-earn-ing capacity. Clearly, the belief that women maximize their wages infemale-friendly occupations, which are alleged to allow easy entryand exit and have low time demands, is inaccurate.

Traditional gender-role ideology contributes to lower observed earn-ings for both males and females, with a slightly higher rate for menthan for women. While its inclusion in both models adds very little tothe R2, the variable is statistically significant. Thus, independent ofthe effects of human capital characteristics, occupational context, andascribed characteristics, one's gender role ideology has a significantnegative impact on earnings. This finding also supports socializationas a partial explanation of the gender-based wage gap. The small in-dependent effect of gender role attitudes does not capture the totalinfluence of such attitudes because they are correlated with othervariables in the analysis. Women who have been socialized to believein the value of traditional roles for women and men are likely tochoose female-dominated jobs, which have low average earnings. Menwho have been socialized to believe in traditional roles for women andmen are likely to think women belong in low-paid, traditionally fe-male jobs. The importance of gender role attitudes is established bythe significant independent relationship and the indirect influencethrough the other variables in the analysis.

Traditional gender role beliefs are declining over time for both menand women and among all race and ethnic groups (Harris & Fire-stone, 1998). To the extent that economic rewards in the form of earn-ings are used to assess the value of traditional gender role expecta-tions, traditional ideologies should continue to decline. In the longrun, less traditional gender role ideologies could lead to more egali-tarian expectations and socialization experiences for men and women,including those related to participation in paid labor and differentialwages. In the short term, such traditional expectations for men andwomen may continue to have detrimental consequences, and bothmen and women should work to overcome them.

210


Notes

1. The dependent variable for this analysis is earnings adjusted to a baseyear of 1986. Ligon (1989) provides an excellent discussion and carefulcomparison of the income measure used in the General Social Survey todata from the Current Population Survey.

2. Ligon suggests using the Pareto distribution to impute a midpoint valuefor the open-ended top category. However, comparing this method to ac-tual earnings data from the Current Population Survey shows that thismethod results in many outliers at the upper level and an increase inheteroscedasticity. Additionally, the earnings variable in the NORC GSShas high positive skewness when using the Pareto method. The approachsuggested by Rosenfeld and Kalleberg (1990) is used in this analysis, as-signing a value equal to the lower limit of the upper category plus onethousand. In doing this, the earnings variable approaches the univariateassumption of normal distribution, making the log of income an unnecess-ary adjustment.

3. Conte (1976) reached the same conclusion when he tested the viability ofthe experience proxy. The mean of the proxy variable for experience was26.44 for males and 26.29 for females. Actual experience in the same dataset had a mean of 24.61 for males and only 12.76 for females. Thus, theexperience proxy overstated women's experience by almost 100%.

4. According to Jaccard, Turrisi, and Wan (1990), it is not necessary in prin-cipal to include an interaction term for age-squared. Therefore, in theinterest of maintaining simplicity of interpretation, an interaction term isnot included in the model in this study.

5. This impact is not large, however, because for the year in which data wereavailable, fewer than 8% of the respondents held more than one job and"periodic" additional employment was not statistically significant with re-spect to earnings.

References

Basow, S. A. (1992) Gender role ideology and the gender based differences in earnings.In Gender: Stereotypes and roles (3rd ed). Pacific Grove, CA: Brooks/Cole.

Becker, G. S. (1971). Human capital: A theoretical and empirical analysis with specialreference to education (2nd ed). NY: Columbia University Press.

Becker, G. S. (1985). Human capital, effort, and the sexual division of labor. Journal ofLabor Economics, 3(1), S33-S58.

Betz, N. E. (1987). Implication of the null environment hypothesis and women's careerdevelopment and for counseling psychology. Counseling Psychologist, 17(1), 136—144.

Bielby, D. D., & Bielby, W. T. (1985). She works hard for the money: Household respon-sibilities and the allocation of effort. Cited in Analyzing gender: A handbook ofsocial science research (p.312). B. B. Hess & M. M. Ferree (Eds). Newbury Park:Sage Publications.

Bryant, W. K. (1991). The economic organization of the household. MA: Cambridge Uni-versity Press.

211


Chaswick, B. (1983), The earnings and human capital of American Jews. Journal ofHuman Resources, 18(3), 313-336.

Chaswick, B. (1985). The labor market status of American Jews: Patterns and determi-nants. American Jewish yearbook, 131-53.

Conte, M. (1976). Labor market discrimination against women. Chapter 9 in Five thou-sand American families—Patterns of economic progress. Vol IV (pp. 257-284). InG. J. Duncan & J. N. Morgan (Eds). ISR: University of Michigan.

Crosby, F. J. (1982). Relative deprivation and working women. NY: Oxford UniversityPress.

Darity, W. Jr., Guilkey, D. K., & Winfrey, W. (1996). Explaining differences in economicperformance among racial and ethnic groups in the USA: The data examined.American Journal of Economics and Sociology, 55(4), 411-425.

Davis, J. A. & Smith, T. W. (1996). General Social Surveys, 1972-1994. [machine-read-able data file]. Principal Investigator, James A. Davis; Director and Co-PrincipalInvestigator, Tom W. Smith. NORC ed. Chicago: National Opinion Research Cen-ter, producer, 1994; Storrs, CT: The Roper Center for Public Opinion Research,University of Connecticut, distributor. 1 data file (32,380 logical records) and 1codebook (p. 1073).

Duncan, G., & Corcoran, M. (1984). Do women 'deserve' to earn less than men? In Dun-can, G. (Ed.) with Coe, R., Corcoran, M., Hill, M., Hoffman, S., & Morgan, J. Years ofpoverty, years of plenty (pp. 153-172). Ann Arbor: University of Michigan, ISR.

Duncan, K. C. (1996). Gender differences in the effect of education on the slope ofexperience-earnings profiles: National Longitudinal Survey of Youth, 1979-1988.American Journal of Economics and Sociology, 55(4), 457-471.

England, P. (1992). Comparable worth: Theories and evidence. NY: Aldine de Gruyter.England, P., & McCreary, L. (1987a). Integrating sociology and economics to study gen-

der and work. In A. Stromberg, L. Larwood, & B. Gutek. (Eds.), Women and work:An annual review. Vol 2 (pp. 143-172). Newbury Park: Sage Publications.

England, P., & McCreary, L. (1987b). Gender inequality in paid employment. In Hess,B. B. & Feree, M. M. (Eds.), Analyzing gender: A handbook of social science re-search (pp. 286-320). Newbury Park: Sage Publications.

Facteau, J. D., & Dobbins, G. H. (1996). Sex bias in performance evaluations. In P. J.Dubeck & K. Borman (Eds.), Women and work: A handbook (pp. 334-338). NewYork: Garland.

Feldberg, R. L. (1987). Women and trade unions: Are we asking the right questions? InC. Bose, R. Feldberg, & N. Sokoloff (Eds), Hidden aspects of women's work (pp.299-322). NY: Praeger.

Filer, R. K. (1983). Sexual differences in earnings: The role of individual personalitiesand tastes. Journal of Human Resources, 18(1), 82-99.

Harris, R. J., & Firestone, J. M. (1998). Changes in predictors of gender role ideologiesamong women: A multivariate analysis. Sex Roles, 38(3/4), 239-252.

Hersch, J. (1991). Male-female differences in hourly wages: The role of human capital,working conditions and housework. Industrial and Labor Relations Review, 44(4),746-759.

Jaccard, J., Turrisai, R., & Wan, C. K. (1990). Interaction effects in multiple regressionseries: Quantitative application in the social sciences. Newbury Park: Sage.

Kalleberg, A. L., & Berg, I. (1987). Work and industry: Structures, markets, and pro-cesses. NY: Plenum.

Kemp, A. A. (1994). Women's work; Degraded and devalued. Englewood Cliffs, NJ:Prentice-Hall.

Kilbourne, B. S., & England, P. (1996). Occupational skill, gender, and earnings. InDubeck, P. J. & Borman, K. (Eds.) Women and work; A handbook (pp. 68-71). NewYork: Garland.

Kilbourne, B. S., England, P., Farkas, G., Beron, K, & Weir, D. (1994). Returns to skill,

212

Juanita M, Firestone, Richard J. Harris, and Linda C. Lambert

compensating differentials, and gender bias: Effects of occupational characteristicson the wages of White women and men. American Journal of Sociology, 100(3),689-719.

Killingsworth, M. E. (1987). Heterogeneous preferences, compensating wage differen-tials and comparable worth. Quarterly Journal of Economics, 102, 727-742.

Kohn, M., & Schooler, C. (1978). The reciprocal effects of the substantive complexity ofwork and intellectual flexibility: A longitudinal assessment. American Journal ofSociology, 84, 24-52.

Lachman, R. (Ed.) (1991). The encyclopedic dictionary of sociology ( 4th ed.). Guilford,CT: The Dushkin Publishing Group, Inc.

Laws, J. L. (1979). The second X: Sex role and social role. NY: Elsevier.Ligon, E. (1989). The development and use of a consistent income measure for the

General Social Survey. University of Chicago: GSS Methodological Report No. 64.Lindsay, P., & Knox, W. E. (1984). Continuity and change in work values among young

adults: A longitudinal study. American Journal of Sociology, 89, 918-31.Major, B., McFarlin, D. B., & Gagnon, D. (1984). Overworked and underpaid: On the

nature of gender differences in personal entitlement. Journal of Personality andSocial Psychology, 47(6), 1399-1412.

Mallan, L. B. (1982). Labor force participation, work experience and the pay gap be-tween men and women. The Journal of Human Resources, 17, 437-448.

Marini, M. M. (1978). Sex differences in the determination of adolescent aspirations: Areview of research. Sex Roles, 4(5), 723-53.

Marini, M. M., & Brinton, M. C. (1984). Sex typing in occupational socialization. In B.Reskin (ed.) Sex segregation in the workplace: Trends, explanations, remedies (pp.192-232). Washington D. C.: National Academy Press.

Marini, M. M., Fan, P. L., Finley, E,. & Beutel, A. M. (1996). Gender and job values.Sociology of Education, 69(1), 49-65.

Mincer, J. (1974). Schooling, experience, and earnings. NY: National Bureau of Eco-nomic Research.

Moen, P. (1992). Women's two roles: A contemporary dilemma. NY: Auburn House.Mortimer, J. T., & Lorence, J. (1979). Work experience and occupational value socializa-

tion: A longitudinal study. American Journal of Sociology, 84, 1361-85.Parcel, T. L., & Mueller, C. W. (1983). Ascription and labor markets: Race and sex

differences in earnings. NY: Academic Press.Polachek, S.W. (1984). Women in the economy: Perspectives on gender inequality. In

Comparable worth: Issue for the 80s (pp. 34-53). NY: Academic Press.Reskin, B. F., & Roos, P. A. (1990). Job queues, gender queues. Philadelphia: Temple

University Press.Rosenfeld, R. A., & Kalleberg, A. L. (1990). A cross-national comparison of the gender

gap in income. American Journal of Sociology, 96(1), 69-106.Shelton, B. A. (1992). Women, men, and time. NY: Greenwood.Snyder, N. M. (1994). Career women in perspective: The Wichita sample. In C. W. Ko-

nek & S. L. Kitch (Eds.), Women and careers: Issues and challenges (pp. 1-18).Thousand Oaks: Sage Publications.

Sorensen, E. (1989). Measuring the effect of occupational sex and race composition onearnings. In R. T. Michael, H. I. Hartmann, & B. O'Farrell (Eds.) Pay equity: Em-pirical inquiries (pp. 49-69). Washington D. C.: National Academy Press.

Sowell, T. (1981). Ethnic America: A history. NY: Basic Books, Inc.Steinberg, R. J. (1990). Social construction of skill: Gender, power, and comparable

worth. Work and Occupations, 17, 449-482.Thacker, R. A. (1995). Gender, influence tactics, and job characteristics preferences:

New insights into salary determination. Sex Roles, 32(9/10), 617-638.U.S. Bureau of the Census. (1994). Labor force, employment, and earnings, http:/ /

www.census.gov/prod/1/gen/95statab/labor.pdf.Ward, K. B., & Mueller, C. W. (1985). Sex differences in earnings: The influence of

213

214 Journal of Family and Economic Issues

industrial sector, authority hierarchy, and human capital variables. Work and Oc-cupations, 12, 437-63.

Woodbury, S. (1993). Culture and human capital: Theory and evidence or theory versusevidence? In Darity, W. Jr. (Ed), Labor economics: Problems in analyzing labormarkets (pp. 239-268). Norwell: Kluver Academic Publishers.

Zill, N., & Rogers, C. C. (1988). Recent trends in the well-being of children in the U. S.and their implications for public policy. In A. J. Cherlin (Ed.), The changing Ameri-can family and public policy (pp. 31-115). Washington D. C.: Urban InstitutePress.

APPENDIX A: Occupations Coded 1 as Involving Authority Skills

Occupation 1980 Census Code

Chief Executives and general administrators, 004

Public administration, Administrators and officials,

public administration 005

Administrators, protective services 006

Financial Managers 007

Personnel and labor relations managers 008

Purchasing managers 009

Managers, marketing, advertising, and public relations 013

Administrators, education and related fields 014

Managers, medicine and health 015

Managers, properties and real estate 016

Postmasters and mail superintendents 017

Funeral directors 018

Managers and administrators, not elsewhere classified 019

Supervisors and proprietors, sales occupations 243

Supervisors, general office 303

Supervisors, computer operators 304

Supervisors, financial records processing 305

Chief communications officers 306

Supervisors, distribution, scheduling, and adjusting clerks 307

Supervisors, tire fighting and fire prevention occupations 413

Supervisors, police and detectives 414

Source: Paula England, 1992


Supervisors, guards 415

Supervisors, food preparation and service occupations 433

Supervisors, cleaning and building service workers 448

Supervisors, personal service occupations 456

Managers, farms, except horticulture 475

Managers, horticulture specialty farms 476

Supervisors, farm workers 477

Supervisors, related agricultural occupations 485

Supervisors, forestry and logging workers 494

Captains and other officers, fishing vessels 497

Supervisors, mechanics and repairers 503

Supervisors, brickmasons, stonemasons, and tile setters 553

Supervisors, carpenters and related workers 554

Supervisors, electricians and power transmission installers 555

Supervisors, painters, paperhangers, and plasterers 556

Supervisors, plumbers, pipefitters and steamfitters 557

Supervisors, construction not elsewhere classified 558

Supervisors, motor vehicle operators 803

Ship captains and mates, except fishing boats 828

Supervisors, material moving equipment operators 843

Supervisors, handlers, equipment cleaners, and laborers, n.e.c. 863

Juanita M. Firestone, Richard J. Harris, and Linda C. Lambert 215

APPENDIX A (Continued): Occupations Coded 1 asInvolving Nurturant Skills


Physicians 084

Dentists 085

Optometrists 087

Podiatrists 088

Health diagnosing practitioners, n e.c. 089

Registered nurses 095

Inhalation therapists 098

Occupational therapists 099

Physical therapists 103

Speech therapists 104

Therapists, n e.c. 105

Physician's assistants 106

Prekindergarten and kindergarten teachers 155

Elementary school teachers 156

Secondary school teachers 157

Special education teachers 158

Teachers, n.ec. 159

Educational and vocational counselors 163

Librarians 164

Social workers 174

Recreation workers 175

Clergy 176

Religious workers 177

Licensed practical nurses 207

Motor vehicles and boats sales workers 263

Apparel sales workers 264

Shoe sales workers 265

Furniture and home furnishing sales workers 266

Radio, television, hi-fi, and appliances sates workers 67

Source: Paula England, 1992.

Occupation

Hardware and building supplies sales workers

Parts sales workers

Other commodities sates workers

Sates counter clerks

Cashiers

Hotel clerks

Transportation ticket and reservation agents

Receptionists

Information clerks. n.e c

Bank letters

Teacher's aides

Child care workers, private household

Bartenders

Waiters and waitresses

Dental assistants

Health aides, except nurses

Elevatoi operators

Barbers

Hairdressers and cosmetologists

Attendants, amusement and recreation facilities

Guides

Usher

Public transportation attendants

Baggage porters and bellhops

Welfare service aides

Child care workers, except private household

Personal service occupations, n.e c.

Taxicab drivers and chauffeurs

Parking lot attendants

1980 Census Code

268

269

274

275

276

317

318

319

323

383

387

406

434

435

445

446

454

457

458

459

463

464

465

466

467

468

469

809

813

gender role ideology and the gender based differences in earnings

Documents