SOLUTION: GENDER DIFFERENCES IN PAY | My Assignment Tutor

NBER WORKING PAPER SERIESGENDER DIFFERENCES IN PAYFrancine D. BlauLawrence M. KahnWorking Paper 7732http://www.nber.org/papers/w7732NATIONAL BUREAU OF ECONOMIC RESEARCH1050 Massachusetts AvenueCambridge, MA 02138June 2000This paper was written while the authors were Visiting Scholars at the Russell Sage Foundation. Wegratefully acknowledge this support. We appreciate the helpful comments of Dora Costa, Marianne Ferber,and Jane Waldfogel, and are especially indebted to the editors of this journal, Alan Krueger, Bradford DeLong, and Timothy Taylor for their constructive and detailed input. Thanks are also due to Abhijay Prakashfor excellent research assistance. The views expressed herein are those of the authors and not necessarilythose of the National Bureau of Economic Research.© 2000 by Francine D. Blau and Lawrence M. Kahn. All rights reserved. Short sections of text not toexceed two paragraphs, may be quoted without explicit permission provided that full credit, including ©notice, is given to the source.Gender Differences in PayFrancine D. Blau and Lawrence M. KahnNBER Working Paper No. 7732June 2000JEL No. J3, J7ABSTRACTWe consider the gender pay gap in the United States. Both gender-specific factors, includinggender differences in qualifications and discrimination, and overall wage structure, the rewards forskills and employment in particular sectors, importantly influence the gender pay gap. Declininggender differentials in the U.S., and the more rapid closing of the gender pay gap in the U.S. thanelsewhere, appear to be primarily due to gender-specific factors. However, the relatively largegender pay gap in the U.S. compared to a number of other advanced countries seems primarilyattributable to the very high level of U.S. wage inequality. Francine D. BlauSchool of Industrial andLabor RelationsLawrence M. KahnSchool of Industrial andLabor RelationsCornell University265 Ives HallIthaca, NY 14853-3901and NBERfdb4@cornell.eduCornell University264 Ives HallIthaca, NY 14853-3901lmk12@cornell.edu Over the past 25 years, the gender pay gap has narrowed dramatically and women haveincreasingly entered traditionally male occupations. These two labor market outcomes are closelylinked, since considerable research suggests that predominantly female occupations pay less, evencontrolling for measured personal characteristics of workers and a variety of characteristics ofoccupations, although the interpretation of such results remains in some dispute.1 In this article, wedescribe these important gains, analyze their sources, and point to some significant remaininggender differences. We also assess where American women stand relative to women in othercountries and conclude with some thoughts about future prospects for the gender pay gap.Overview of Gender Differences and TrendsEarningsGender earnings disparities in the United States have shown considerable recentconvergence. Figure 1 shows the trends in the female-male earnings ratio for annual earnings ofyear-round, full-time workers and for usual weekly earnings of full-time workers. These measurescan be thought of as adjusting for the fact that women as a group tend to work fewer weeks per yearand hours per week than men. (Government data are not available for wage rates over this period.)The data indicate that the gender ratio was roughly constant at about 60 percent from the late 1950sto about 1980. Indeed, as Fuchs (1971, p. 9) pointed out, this longstanding ratio had a biblicalantecedent in Leviticus (27:1-4), where it is decreed that a woman is worth 30 shekels of silver anda man 50 shekels. The gender earnings ratio began to increase in the late 1970s or early 1980s.Convergence has been substantial: between 1978 and 1999 the weekly earnings of women full-time1. See, for example, Sorensen (1990). A recent study by Macpherson and Hirsch (1995) using a 1973-93 panel of datafrom the Current Population Survey finds that the negative wage effect of percent female in the occupation is reduced byat least two-thirds when occupational characteristics are included and longitudinal wage change models are estimated tocontrol for unobserved fixed effects.2workers increased from 61 percent to 76.5 percent of men’s earnings. However, the ratio appears tohave plateaued in the mid-1990s.2This increase in the gender earnings ratio could represent either the entry of new cohortsinto the labor market, each one better prepared and possibly encountering less discrimination thanprevious ones, or an upward progression over time in the gender ratio within given cohorts, or somecombination of the two. Table 1 sheds light on this question by presenting gender ratios for hourlywages of full-time workers, disaggregated by age, from the 1979, 1989 and 1999 AnnualDemographic Files of the Current Population Survey. These years span the period of greatestconvergence in the gender pay gap. Since wages are calculated by dividing last year’s annual wageand salary income by annual hours (i.e., usual hours per week multiplied by weeks worked), thisyields data on wages for the previous calendar year.3 We focus on full-time workers to identify amore homogeneous group of men and women workers and so that our computation of the genderpay gap is not affected by any hourly wage penalty for part-time work.In any given year, looking down the columns of Panel A in Table 1, the gender wage ratiotends to decline with age. But over time, looking across the rows in the same panel, the genderwage ratio has increased for almost every age group. These “between cohort” changes, which arecalculated in Panel B, indicate that each new cohort of women is indeed faring better than previousones. Gains for the two youngest cohorts were heavily concentrated in the 1980s (and, to a lesser2. Of course, money wages are an incomplete indicator of total compensation, which would take into account not onlynonwage benefits but also compensating differentials for job amenities. This is far from a trivial issue. Differing jobamenities may be especially important, given the likelihood of substantial differences in occupational preferencesbetween men and women. Complex issues are also raised with respect to nonwage benefits since, in some instances,married workers may be covered under their spouses’ plans, thus reducing their demand for these benefits.Unfortunately, the relevant data and prior research needed for an investigation of these issues are considerably sparserthan one would like, and a full consideration of these issues would take us well beyond the scope of this paper.3. The sample for each year includes full-time, wage and salary workers aged 18-64 who participated in the labor forceat least 27 weeks. Those earning less than $2.70 or more than $241.50 in 1998 dollars, using the GDP Implicit PriceDeflator for Personal Consumption Expenditures, are excluded, as are individuals with allocated wage and salaryincome. Results were not sensitive to these sample exclusions. Top-coded values of wage and salary income wereevaluated at 1.45 times the top-coded value. All wages are weighted using the CPS sampling weights. Here and inwhat follows, means and associated ratios are computed based on geometric means which may differ somewhat fromarithmetic means in placing less emphasis on extreme values.3extent, in the 1970s prior to our sample period; see Blau, 1998). Increases for women 35-54 weremore evenly spread over the 1980s and 1990s, whereas substantial gains for women over 54 did notappear until the 1990s. Over the whole 20-year period, cumulative increases in the ratio were quitecomparable for all groups under 55, ranging from 11.7 percentage points for the 18-24 age group to17.2 percentage points for 35-44 year olds.Since the Current Population Survey, from which these data are drawn, is nationallyrepresentative, some indication of changes over time within cohorts can be gained by comparing thegender ratio among, for example, men and women aged 25-34 in 1978 to the ratio among men andwomen aged 35-44 in 1988.4 These changes may be seen by looking diagonally across entries inPanel A of Table 1 and have been computed as the “within cohort” changes in Panel B. Note that incalculating the within cohort changes, the ratio for the youngest age group, those 18-24, iscompared to the ratio for those aged 28-34 ten years later (a group not shown in Panel A). For bothperiods, the within cohort changes for women in the two younger age groups are negative,indicating that women under 35 lost ground relative to men as they aged. The declines wererelatively small in 1980s but more substantial in the 1990s. Women in the older two age groupsexperienced within cohort increases in their wages relative to men’s, further closing the gender gapas they aged. Over the whole 1978-98 period, the cohort that was 18-24 years old in 1978experienced a 6.9 percentage point fall in the gender earnings ratio; in contrast, the cohorts thatwere 25-34 and 35-44 years old in 1978 saw 1.3 and 10.4 percentage point gains, respectively, overthe next twenty years.Thus, while the narrowing of the gender gap has primarily been associated with the entry ofnew cohorts, each faring better than their predecessors, within cohort earnings growth has alsoplayed a role for older women. These results suggest some caution in assessing women’s gains in4. These comparisons will be affected by self-selection into employment of men and women in each year. Given thelarger changes in female labor force participation, this is likely to be a greater problem for women. In addition, it is wellknown that one cannot simultaneously identify age, period and cohort effects. For example, an increase in the wageratio for successive cohorts, rather than a cohort effect, could simply reflect a difference in economic conditions betweenthe two time periods.4the labor market by focusing on the relatively small gender gap among younger cohorts in recentyears (for an example, see Furchtgott-Roth and Stolba, 1999, p. xvii). The relatively high wageratios of younger women tend to decline as they age, likely reflecting the greater tendency ofwomen to drop out of the labor force for family reasons and also perhaps the greater barriers to theiradvancement at higher levels of the job hierarchy, an issue we will discuss further below.OccupationsFor many decades, one of the most salient features of women’s status in the labor marketwas their tendency to work in a fairly small number of relatively low-paying, predominantly femalejobs.5 Women were especially concentrated in administrative support (including clerical) andservice occupations. In the early 1970s, 53 percent of women workers were in such jobs, comparedto only 15 percent of men. At that time, less than one in five managers were women, and women inprofessional positions were frequently employed in traditionally female professions, like nurse, prekindergarten and kindergarten teacher, elementary school teacher, dietitian, or librarian, which alsotend to be relatively low-paying compared to predominantly male professional occupations.Women were also underrepresented in blue-collar jobs, including higher-paying precisionproduction and craft occupations.All this began to change in the 1970s and, although many of the broad outlines of theseoccupational differences between men and women remain, the disparities have been much reduced.Women are now less concentrated in administrative support and service occupations, with 41percent holding such jobs in 1999 compared to (still) 15 percent of men. Women are now 45percent of those in managerial jobs. Indeed, significant numbers of women have moved into avariety of traditionally male jobs throughout the occupational spectrum. A particularly dramaticexample of desegregation can be seen in the jobs of female college graduates. Almost half ofwomen who graduated college in 1960 became teachers, while in 1990, less than 10 percent did so5. The following data are taken from Blau, Ferber and Winkler (1998) and the United States Bureau of Labor Statistics(BLS) Web site.5(Flyer and Rosen, 1994, p. 28).The degree of segregation by sex across the hundreds of detailed occupations listed by theBureau of the Census is often summarized by the Index of Segregation, which gives the percentageof women (or men) who would have to change jobs for the occupational distribution of the twogroups to be the same.6 After remaining at about two-thirds for each Census year since 1900, thisindex fell from 67.7 in 1970 to 59.3 in 1980 and 52.0 in 1990 (Blau, Simpson and Anderson 1998;Blau, Ferber and Winkler 1998). The principal cause of the reduction was the movement of womeninto predominantly male jobs, although changes in the mix of occupations toward occupations thathad been more integrated by gender also played a role (Blau, Simpson and Anderson, 1998).Some indication of trends over the 1990s may be obtained using Current Population Surveydata based on a somewhat different set of occupations and workers. The Index of Segregationcomputed from this source decreased from 56.4 in 1990 to 53.9 in 1997 (Jacobs, 1999), yielding anannual decrease of .4 percentage points over the 1990s, compared to .8 and .6 percentage points inthe 1970s and 1980s, respectively. Thus, the long-term reduction in occupational segregation bysex appears to have continued into the 1990s, but at a slower pace.While one can find examples of significant changes in sex composition in all types of jobs,women have had considerably greater success in entering previously male white-collar and serviceoccupations than blue-collar categories. There has also been a tendency for some jobs to switchfrom predominantly male to predominantly female as women enter them. For example, between1970 and 1990, women increased their share of typesetters and compositors from 17 to 70 percent;of insurance adjusters, examiners, and investigators from 30 to 71 percent; and of public relationsspecialists from 27 to 59 percent (Blau, Simpson and Anderson 1998).An additional qualification is that calculations like these, based on aggregate national datafrom the Census or the Current Population Survey, are likely to understate the full extent of6. The index of segregation is calculated as ½Σimi – fi, where mi = the percentage of all male workers employed inoccupation i and fi = the percentage of all female workers employed in occupation i.6employment segregation of women because employers’ job categories are far more detailed thanthose used by the Census. Thus, some Census listings probably combine individual job categoriesthat are predominantly male with some that are predominantly female, producing apparentlyintegrated occupations. Moreover, even in occupations where both sexes are substantiallyrepresented, women are often concentrated in lower-paying industries and firms (Blau, 1977,Groshen, 1991; Bayard, Hellerstein, Neumark and Troske, 1999).Explaining the Gender Pay Gap and Occupational SegregationTraditionally, economic analyses of the gender pay gap and occupational segregationhave focused on what might be termed gender-specific factors, that is, gender differences ineither qualifications or labor market treatment of similarly qualified individuals. More recently,following on the work of Juhn, Murphy and Pierce (1991) on trends in race differentials, someadvances have been made by considering the gender pay gap and other demographic paydifferentials in the context of the overall structure of wages. Wage structure is the array of pricesdetermined for labor market skills and the rewards to employment in particular sectors.Gender-Specific FactorsGender differences in qualifications have primarily been analyzed within the humancapital model (Mincer and Polachek, 1974). Given the traditional division of labor by gender inthe family, women tend to accumulate less labor market experience than men. Further, becausewomen anticipate shorter and more discontinuous work lives, they have lower incentives toinvest in market-oriented formal education and on-the-job training, and their resulting smallerhuman capital investments will lower their earnings relative to those of men. The longer hoursthat women spend on housework may also decrease the effort they put into their market jobscompared to men, controlling for hours worked, and hence also reduce their productivity andwages (Becker, 1985).7To the extent that women choose occupations for which on-the-job training is lessimportant, gender differences in occupations would also be expected. Women may especiallyavoid jobs requiring large investments in skills which are unique to a particular enterprise,because the returns to such investments are reaped only as long as one remains with thatemployer. At the same time, employers may be reluctant to hire women for such jobs becausethe firm bears some of the costs of such firm-specific training, and fears not getting a full returnon that investment.Labor market discrimination may also affect women’s wages and occupations.Discrimination can arise in a variety of ways. In Becker’s (1957) model, discrimination is due tothe discriminatory tastes of employers, co-workers, or customers. Alternatively, in models of“statistical discrimination,” differences in the treatment of men and women arise from averagedifferences between the two groups in the expected value of productivity (or in the reliabilitywith which productivity may be predicted), which lead employers to discriminate on the basis ofthat average (for example, Aigner and Cain, 1977). Finally, discriminatory exclusion of womenfrom “male” jobs can result in an excess supply of labor in “female” occupations, depressingwages there for otherwise equally productive workers, as in Bergmann’s (1974) “overcrowding”model.Wage StructureWage structure is a factor not directly related to gender which may nonetheless influencethe size of the gender gap in pay. Although it has only been recognized recently, the humancapital model and models of discrimination potentially imply an important role for wagestructure in explaining the gender gap. If, as the human capital model suggests, women have lessexperience than men, on average, the higher the return to experience received by workers,regardless of sex, the larger will be the gender gap in pay. Similarly, if, due to discrimination orother factors, women tend to work in different occupations and industries than men, the higherthe premium received by workers, both male and female, for working in the male sector, the8larger will be the gender pay gap.Evidence on Human Capital, Discrimination, and the Gender Pay GapThe typical approach to analyzing the sources of the gender pay gap is to estimate wageregressions specifying the relationship between wages and productivity-related characteristics formen and women. The gender pay gap may then be statistically decomposed into twocomponents: one due to gender differences in measured characteristics, and the other“unexplained” and potentially due to discrimination. Such empirical studies provide evidenceconsistent with both human capital differences and labor market discrimination in explaining thegender pay gap.But any approach which relies on a statistical residual will be open to question as towhether all the necessary independent variables were included in the regression. For example,even if measured human capital characteristics can explain only a portion of the wage gapbetween men and women, it is possible that unmeasured group differences in qualifications mayexplain part of the residual. If men are more highly endowed with respect to these omittedvariables then we would overestimate discrimination. Alternatively, if some of the factorscontrolled for in such regressions — like occupation and tenure with the employer — themselvesreflect the impact of discrimination, then discrimination will be underestimated. Moreover, ifwomen face barriers to entry into certain occupations, they may have higher unmeasuredproductivity than men in the same jobs. This factor would also suggest an underestimate ofdiscrimination if we controlled for occupation.Using the residual from a regression to estimate the effects of discrimination will also runinto trouble if feedback effects are important. Even small initial discriminatory differences inwages may cumulate to large ones as men and women make decisions about human capitalinvestments and time allocation in the market and the home on the basis of these wagedifferentials.9Results of such studies may nonetheless be instructive. Representative findings fromanalyses of this type may be illustrated by results from Blau and Kahn (1997). Using data from thePanel Study of Income Dynamics (PSID), which contains information on actual labor marketexperience for a large, nationally representative sample, we found a wage differential betweenmale and female full-time workers in 1988 of 27.6 percent. We first considered the differenceafter taking education, labor market experience, and race into account (the “human capitalspecification”) and then additionally controlled for occupation, industry and unionism.In the human capital specification, gender differences in the explanatory variablesaccounted for 33 percent of the total gender gap. While gender differences in educationalattainment were small, the gender gap in full-time work experience was substantial, 4.6 years, onaverage, and accounted for virtually all of the explained portion of the gender gap in thisspecification. When occupation, industry and unionism were also taken into account, theexplained portion of the gap rose to 62 percent of the total gender gap, suggesting that aconsiderable portion of the gap (62-33=29 percent) was due to wage differences between menand women with similar human capital working in different industries or occupations or in unionvs. nonunion jobs. Putting these results in terms of the gender wage ratio, we found that theunadjusted ratio was 72.4 percent. Adjusting for human capital variables only increased the ratioto 80.5 percent; and adjusting for all variables raised the ratio to 88.2 percent.While the unexplained gender gap was considerably smaller when all variables weretaken into account (38 percent of the total gender gap) than when only human capital variableswere considered (67 percent of the total gender gap), a substantial portion of the pay gapremained unexplained and potentially due to discrimination in both specifications. And, as wesuggested above, including controls for occupation, industry, and union status may bequestionable to the extent that they may be influenced by discrimination.Nonetheless, the residual gap, however measured, may well reflect factors apart fromdiscrimination. One that has received particular attention recently is the impact of children onwomen’s wages, since evidence of a negative effect of children on wages has been obtained, even10in analyses which control for labor market experience (Waldfogel, 1998). The reason may bethat, in the past, having a child often meant that a woman withdrew from the labor force for asubstantial period, breaking her tie to her employer and forgoing the returns to any firm-specifictraining she might have acquired, as well as any rewards for having made an especially good jobmatch.Some recent studies on discrimination have taken different approaches to the question,thus avoiding some of the problems of traditional analyses. First, two studies have appliedtraditional econometric techniques to especially homogeneous groups and employed extensivecontrols for qualifications, thus minimizing the effect of gender differences in unmeasuredcharacteristics. Wood, Corcoran, and Courant (1993) studied graduates of the University ofMichigan Law School classes of 1972-1975, 15 years after graduation. The gap in pay betweenwomen and men was relatively small at the outset of their careers, but 15 years later, womengraduates earned only 60 percent as much as men. Some of this difference reflected choiceswhich workers had made, including the propensity of women lawyers to work shorter hours.But, even controlling for current hours worked, as well as an extensive list of workerqualifications and other covariates, including family status, race, location, grades while in lawschool, and detailed work history data, such as years practiced law, months of part-time work,and type and size of employer, a male advantage of 13 percent remained. In a similar vein,Weinberger (1998) examined wage differences among recent college graduates in 1985. Hercontrols included narrowly defined college major, college grade point average, and specificeducational institution attended. She found an unexplained pay gap of 10 to 15 percent betweenmen and women.A second set of studies used an experimental approach. Neumark (1996) analyzed theresults of a hiring “audit” in which male and female pseudo-job seekers were given similarrésumés and sent to apply for jobs waiting on tables at the same set of Philadelphia restaurants.In high-priced restaurants, a female applicant’s probability of getting an interview was 40percentage points lower than a male’s and her probability of getting an offer was 50 percentage11points lower. A second study examined the impact of the adoption of “blind” auditions bysymphony orchestras in which a screen is used to conceal the identity of the candidate (Goldinand Rouse, forthcoming). The screen substantially increased the probability that a woman wouldadvance out of preliminary rounds and be the winner in the final round. The switch to blindauditions was found to explain between 25 and 46 percent of the increase in the percentagefemale in the top five symphony orchestras in the United States, from less than 5 percent of allmusicians in 1970 to 25 percent today.Third, several recent studies have examined predictions of Becker’s (1957) discriminationmodel. Becker and others have pointed out that competitive forces should reduce or eliminatediscrimination in the long run because the least discriminatory firms, which hire more lowerpriced female labor, would have lower costs of production and should drive the morediscriminatory firms out of business. For this reason, Becker suggested that discriminationwould be more severe in firms or sectors that are shielded to some extent from competitivepressures. Consistent with this reasoning, Hellerstein, Neumark and Troske (1997) found that,among plants with high levels of product market power, those employing relatively more womenwere more profitable. In a similar vein, Black and Strahan (1999) report that, with thederegulation of the banking industry beginning in the mid-1970s, the gender pay gap in bankingdeclined.Finally, additional evidence on discrimination comes from court cases. A number ofemployment practices which explicitly discriminated against women used to be quite prevalent;including marriage bars restricting the employment of married women (Goldin 1990), and theintentional segregation of men and women into separate job categories with associated separateand lower pay scales for women (e.g., Bowe v. Colgate-Palmolive Co., 416 F.2d 711 {7th Cir.1969}; IUE v. Westinghouse Electric Co., 631 F.2d 1094 {3rd Cir. 1980}). While many suchovert practices have receded, recent court cases suggest that employment practices still existwhich produce discriminatory outcomes for women.For example, in 1994, Lucky Stores, a major grocery chain, agreed to a settlement of12$107 million after Judge Marilyn Hall Patel found that “sex discrimination was the standardoperating procedure at Lucky with respect to placement, promotion, movement to full-timepositions, and the allocation of additional hours” (Stender v. Lucky Stores, Inc. 803 F. Supp. 259;{N.D. Cal. 1992}; King 1997). And, in 2000, the U.S. Information Agency agreed to pay $508million to settle a case in which the Voice of America rejected women who applied for highpaying positions in the communications field. A lawyer representing the plaintiffs said that thewomen were told things like, “These jobs are only for men,” or “We’re looking for a male voice”(FEDHR 2000). A final example is the 1990 case against Price Waterhouse, a major accountingfirm, in which the only woman considered for a partnership was denied, even though, of the 88candidates for partner, she had brought in the most business. Her colleagues criticized her forbeing “overbearing, ‘macho’ and abrasive and said she would have a better chance of makingpartner if she would wear makeup and jewelry, and walk, talk and dress ‘more femininely.’” TheCourt found that Price Waterhourse maintained a partnership evaluation system that “permittednegative sexually stereotyped comments to influence partnership selection” (BNA 1990; Lewin1990).Analyzing the Trends in the Gender Pay GapThe narrowing of the gender gap in recent years has taken place in an environment ofsharply rising wage inequality. This raises a paradox. Women continue to have less experiencethan men, on average, and continue to be located in lower-paying occupations and industries. Asthe rewards to higher skills and the wage premia for employment in occupations and industrieswhere men are more heavily represented have risen, women should have been increasinglydisadvantaged (Blau and Kahn, 1997). How can we explain the decrease in the gender pay gap inthe face of overall shifts in labor market prices that should have worked against women as agroup?To answer this question, we summarize results from Blau and Kahn (1997), where we13made use of decomposition techniques developed by Juhn, Murphy and Pierce (1991). The studyanalyzed women’s wage gains over the 1980s, which, as noted in Figure 1 and Table 1, was aperiod of exceptionally rapid closing of the gender wage gap. We found that rising inequalityand higher rewards to skills did indeed retard wage convergence during this period but this wasmore than offset by improvements in gender-specific factors. First, the gender gap in full-timeexperience fell from 7.5 to 4.6 years over this period (see also O’Neill and Polachek, 1993).Second, the relative proportion of women employed as professionals and managers rose, whiletheir relative representation in clerical and service jobs fell. Third, the declining unionizationrate had a larger negative impact on male than female workers, since union membership declinedmore for men than women. Fourth, also working to reduce the gender pay gap was a decrease inthe size of the unexplained gender gap.The decline in the unexplained gender wage gap that occurred over the 1980s may reflecteither an upgrading of women’s unmeasured labor market skills, a decline in labor marketdiscrimination against women, or a combination of the two. Both interpretations are credibleduring this period.Since women improved their relative level of measured skills, as shown by the narrowingof the gap in full-time job experience, it is plausible that they also enhanced their relative level ofunmeasured skills. For example, women’s increasing labor force attachment may haveencouraged them to acquire more on-the-job training. Evidence also indicates that genderdifferences in college major, which have been strongly related to the gender wage gap amongcollege graduates (Brown and Corcoran, 1997), decreased over the 1970s and 1980s (Blau,Ferber and Winkler, 1998); the marketability of women’s education has probably improved. Themale-female difference in SAT math scores has also been declining, falling from 46 points in1977 to 35 points in 1996 (Blau, 1998), which could be another sign of improved quality ofwomen’s education.The argument that discrimination against women declined in the 1980s may seem lesscredible than that the unmeasured human capital characteristics of women improved, since the14federal government scaled back its anti-discrimination enforcement effort during the 1980s(Leonard, 1989). However, as women increased their commitment to the labor force andimproved their job skills, the rationale for statistical discrimination against them diminished; thusit is plausible that this type of discrimination declined. And, in the presence of feedback effects,employers’ revised views can generate further increases in women’s earnings by raising theirreturns to investments in job qualifications and skills. To the extent that such qualifications arenot fully controlled for in the wage regression used to decompose the change in the gender wagegap, this may also help to explain the decline in the “unexplained” gap. Another possible reasonfor a decline in discrimination against women is that changes in social attitudes have made suchdiscriminatory tastes increasingly unpalatable.Finally, the underlying labor market demand shifts which widened wage inequality overthe 1980s may have favored women relative to men in certain ways, and thus contributed to adecrease in the unexplained gender gap. The impact of technological change included withinindustry demand shifts that favored white collar workers in general (Berman, Bound andGriliches, 1994). Given the traditional male predominance in blue-collar jobs, this shift might beexpected to benefit women relative to men, possibly off-setting the large increase in femalesupply that occurred during this time (Blau and Kahn 1997). In addition, increased computer usefavors women both because they are more likely than men to use computers at work and becausecomputers restructure work in ways that de-emphasize physical strength (Krueger 1993;Weinberg, 2000).The narrowing of the gender pay gap decelerated over the 1990s, as shown in Figure 1. Itwill not be possible to do for this period the type of detailed decomposition reported above forthe 1980s for a few more years, since data on actual labor market experience are crucial and thePSID (final release) data, which are unique in having this information for a nationallyrepresentative cross-section of individuals, are not yet available past 1993 (with 1992 wageinformation).However, using data from the Current Population Surveys, we can shed some light on the15relative importance of gender-specific factors versus wage structure in explaining changes in thegender pay gap in the 1990s compared to the 1980s. The trends in the CPS data summarized inTable 2 mirror those noted from various sources. The gender wage ratio rose in both the 1980sand the 1990s, but rose more rapidly in the 1980s. The narrowing of the gender gap wasaccompanied by substantial real wage growth for women in comparison to little change in realwages for men. The data also show rising wage inequality over the period for both men andwomen, as measured by the standard deviation of the log of wages, but inequality rose faster inthe 1980s than in the 1990s. Table 2 also shows that the trends in the gender ratio estimatedusing fixed-weight averages — that is, holding the relative size of age and education groups attheir 1979 levels — are quite similar to those for the actual ratio.7 This suggests that the morerapid closing of the gender gap in the 1980s cannot be explained by a change in the compositionof the male and female labor forces along these dimensions.Table 2 also indicates that women’s wages moved steadily up the distribution of malewages over this period, from an average percentile of 26.0 in 1979 to 38.5 in 1999.8 The fact thatthe pace of this upward movement was higher in the 1980s than the 1990s suggests that changesin gender-specific factors were more favorable for women in the 1980s than in the 1990s.How much would the gender-specific changes have decreased the gender pay gap if theoverall distribution of wages had not become more unequal over this time? The last row of Table2 shows what the gender ratio would have been in each year if male wage inequality hadremained at its 1978 levels. These ratios are computed by giving a man or woman at, say, the25th percentile of the male wage distribution in 1988 (or 1998) a wage equal to a male at the 25thpercentile of the male wage distribution in 1978. The results indicate that, as expected, thegender ratio would have increased faster over the 1978-98 period had wage inequality not risen.7. The age groups were: 18-24, 25-34, 35-44, 45-54 and 55-65; the education groups were: less than 12 years, 12 years,13-15 years, and 16 or more years.8. These rankings are obtained by first finding each individual woman’s percentile in the male wage distribution in eachyear and then finding the female mean of these percentiles. As in our descriptive statistics on wages, we use the CPSsampling weights in forming the percentiles of the male wage distribution.16Specifically, under a constant wage structure, the gender pay ratio would have risen by 15.2percentage points, a modestly higher rate of convergence that the actual increase of 12.7percentage points. However, the disparity between the two subperiods is actually greater for themeasure which holds the distribution of wages constant, meaning that trends in wage inequalitydo not help to explain women’s smaller gains in the 1990s.9 Putting this somewhat differently,gender-specific factors are more than sufficient to account for the difference in convergencebetween the two periods. This suggests that improvements in women’s qualifications must havebeen greater and/or the decline in discrimination against women must have been larger in the1980s than in the 1990s.Could differential shifts in the supply of female workers between these two periods helpto explain the slower convergence in the 1990s? It has been pointed out, for example, that recentwelfare reforms and other government policies spurred an increase in employment among singlemothers (see, for example, Meyer and Rosenbaum 1999). Yet, despite these increases, femalelabor force participation overall increased considerably more slowly over the 1990s than over the1980s, both absolutely and relative to the male rate (Costa 2000, Figure 1; and BLS Website).Thus, on its face rising female labor supply is not a plausible explanation for the difference inwage convergence in the two decades. The growth in participation among single heads, who tendon average to be less well educated than other women, could also have slowed wage convergenceby shifting the composition of the female labor force toward low-wage women. But as we saw inTable 2, when trends in the gender ratio were estimated using fixed-weight averages — that is,controlling for age and education –- the difference between the rate of convergence in the 1980sand 1990s remains.Our identification of the relative importance of gender-specific factors and wage structurein explaining wage convergence of men and women in the 1980s and 1990s is based on someassumptions which, although not unreasonable, should be noted. This approach is based on two9. Results were similar when the 1988 or 1998 male wage distributions were used to evaluate the current yearpercentiles.17complementary assumptions: 1) in each year, gender-specific factors, including differences inqualifications and the impact of labor market discrimination, determine the percentile ranking ofwomen in the male wage distribution; and 2) overall wage structure, as measured by themagnitude of male wage inequality, determines the wage penalty associated with women’s lowerposition in the wage distribution.This framework assumes that male wage inequality is determined by forces outside thegender pay gap and is a useful indicator of the price of skills affecting both men and women.Consistent with this approach is evidence that widening wage inequality in the 1980s and 1990swas importantly affected by economy-wide forces, including technological change, internationaltrade, the decline in unionism, and the falling real value of the minimum wage (Katz and Autor,1999). And, rises in wage inequality during this period were similar for men and women. Thissuggests that the decomposition in the last row of Table 2 is reasonable. However, we cautionthe reader that, under some circumstances, the gender pay gap could influence male inequality.For example, Fortin and Lemieux (1998) present a model in which a falling gender pay gapcauses rising male wage inequality, as women displace men in a fixed job hierarchy.10Sources of Gender Differences in OccupationsThere is considerable evidence to support the belief that gender differences in preferencesplay some role in gender differences in occupations (Gunderson, 1989). The claim thatdiscrimination is also important is more controversial. It is not an easy matter to distinguishbetween the two empirically and, of course, both preferences and discrimination may contribute10. The presence of discrimination can also complicate the interpretation of this decomposition (Juhn, Murphy andPierce 1991; Blau and Kahn 1996b and 1997; Suen 1997). In particular, Suen suggests a model in whichdiscrimination takes the form of a fixed deduction from every woman’s pay, say 20 percent. This may produce amechanical negative relationship between male wage inequality and the average female percentile: anything thatincreases male inequality will push more men below the average woman. However, Table 2 shows that the genderpay ratio increased as the mean female percentile rose, suggesting that the increase in the female percentile is notsimply an artifact of widening male inequality, but rather contains information about women’s relative qualificationsand treatment.18to observed differences.Some persuasive evidence of the importance of discrimination comes from descriptionsof institutional barriers that have historically excluded women from particular pursuits orimpeded their upward progression (Reskin and Hartmann, 1986). In addition many studies,although not all, have found that women are less likely to be promoted, all else equal (see, forexample, Cobb-Clark and Dunlop, 1999; McCue, 1996; Hersch and Viscusi, 1996). It has alsobeen found that a major portion of the gender difference in on-the-job training remainsunexplained, even after gender differences in predicted turnover probability and other variablesare taken into account, suggesting that discrimination may play a role in this respect as well(Royalty 1996).11 Such studies of promotion and training are certainly suggestive ofdiscrimination, but they suffer from the standard problems of this type of exercise discussed inconnection with decompositions of the gender pay gap.Is there a glass ceiling impeding women’s occupational advancement, as some havealleged? Disparities at the upper levels of many professions are easy to document. In academia,for example, women constituted 44.7 percent of assistant professors in 1994-95, compared to31.2 percent of associate and 16.2 percent of full professors (Blau, Ferber and Winkler, 1998). Inbusiness, a federal Glass Ceiling Commission (1995) found that women comprise only 3 to 5percent of senior managers in Fortune 1000 companies.While the disparities are obvious, the reasons behind them are harder to pin down. Suchdisparities may be due in whole or part to the more recent entry of women into these fields andthe time it takes to move up the ladder. Data in each case do suggest some female gains overtime. For example, women’s share of associate professors in 1995 (31.2 percent) wasconsiderably higher than their 1985 level (23.3 percent) and nearly equal to their share ofassistant professors a decade earlier (35.8 percent). However, the female share of full professorsin the mid-1990s, at 16.2 percent, although higher than the 11.6 percent of full professors who11. For a review of evidence that women have traditionally received less on-the-job training than men, see Barron,Black and Loewenstein (1993).19were women in the mid-1980s, was still considerably below the 23.2 percent of associateprofessors who were women in 1985 (Blau, Ferber and Winkler, 1998).Despite recent changes, there is some evidence suggesting that discrimination plays a rolein academia. A recent study of faculty promotion in the economics profession found that,controlling for quality of Ph.D. training, publishing productivity, major field of specialization,current placement in a distinguished department, age and post-Ph.D. experience, femaleeconomists were still significantly less likely to be promoted from assistant to associate and fromassociate to full professor — although there was also some evidence that women’s promotionopportunities from associate to full professor improved in the 1980s (McDowell, Singell andZiliak, 1999). In a similar vein, a recent report on faculty at MIT finds evidence of differentialtreatment of senior women and points out that it may encompass not simply differences in salarybut also in space, awards, resources and responses to outside offers, “with women receiving lessdespite professional accomplishments equal to those of their male colleagues” (MIT, 1999, p. 4).Even in occupations where good data exist on the availability of women in the lowerranks, as in academia, it is difficult to determine whether the degree of movement of womenthrough the ranks is sufficient to confirm or disprove notions that women face special barriers. Itis still harder in other areas where such data do not exist and where norms regarding the speed ofupward movement are less well defined.However, a recent study of executives does highlight the substantial impact on pay ofgender differences in level of the job hierarchy and firm, although it does not shed light on thecauses of such differences. For a sample of the five highest-paid top executives among a largegroup of firms, Bertrand and Hallock (1999) found that the 2.5 percent of the executives whowere women earned 45 percent less than their male counterparts. Three-quarters of this gap wasdue to the fact that women managed smaller companies and were less likely to be the CEO, chairor president of their company. Only 20 percent was attributable to female executives beingyounger and having less seniority. Female executives made some gains over the 1992-97 sampleperiod: the fraction of women in these top-level jobs rose from 1.29 to 3.39 percent; their relative20compensation increased from 52 to 73 percent; and their representation at larger corporationsrose. There was, however, no increase in women’s representation in the top occupations of CEO,chair, vice-chair, or president.The role of occupational upgrading in narrowing the gender pay gap, as well as theevidence that the glass ceiling may be showing some hairline cracks, raises the question of whyoccupational differences between men and women have declined. Both the human capital andthe discrimination models potentially provide viable explanations.12 On the one hand, it may bethat as women anticipated remaining in the labor force for longer periods it became profitable forthem to invest in the larger amount of career-oriented formal education and on-the-job trainingoften required in traditionally male occupations. On the other hand, women may have enteredthese areas in response to declining barriers to their participation. And, the rise in women’sacquisition of career-oriented formal education may reflect, not only changes in women’spreferences and their response to greater market opportunities, but also changes in the admissionpractices of educational institutions with the passage of Title IX in 1972 banning sexdiscrimination in education and other social pressures. The increase in women’s representationin professional schools has been truly remarkable. Between 1966 and 1993, women’s share ofdegrees rose from 6.7 to 37.7 percent in medicine, 3.8 to 42.5 percent in law, 3.2 to 34.6 percentin business, and 1.1 to 33.9 percent in dentistry (Blau, Ferber and Winkler 1998). While it islikely that both changes in women’s behavior and changes in the amount of discrimination theyfaced played a role in women’s occupational shifts, we are not aware of any research unravelingthis complex causation.The U.S. Gender Pay Gap in International Perspective12. England (1982) provides the strongest critique of the human capital explanation for occupational segregation. Someparticularly interesting recent evidence implicitly supporting the human capital model is Macpherson and Hirsch’s(1995) finding of a substantial effect of skills in explaining the lower pay in predominantly female jobs. Their estimatesare among the higher ones; for a review of past evidence, see Sorensen (1990).21How does the pay gap faced by U.S. women compare to that faced by women in othercountries? Table 3 shows female-male weekly earnings ratios of full-time workers for the UnitedStates and a number of other advanced countries over the 1979-98 period, based on unpublishedOECD tabulations from nationally-representative microdata sets. In 1979-81, the U.S. genderpay ratio was 62.5 percent, nearly 9 percentage points below the 71.2 percent average for theother countries listed here. However, the U.S. gender pay ratio increased at a faster rate in the1980s and 1990s than it did elsewhere. By 1994-98, it was 76.3 percent, only marginally belowthe non-U.S. average of 77.8 percent. Nonetheless, the gender earnings ratio was higher in eightout of 16 other countries than it was in the United States, often considerably so. How do weexplain why U.S. women do not rank higher relative to their counterparts in other advancedcountries? And, what accounts for the faster narrowing of the gender gap in the U.S.?There seems to be little reason to believe that U.S. women are either less well qualifiedcompared to men than women in other countries where the gender pay gap is considerablysmaller, or encounter more discrimination than women in those other countries. While data onactual labor market experience are not generally available, some indirect indicators suggest thatU.S. women tend to be relatively more committed to the labor force then women in many of theother countries. Female labor force participation rates are relatively high in the United States, asis the share of employed women working full time. Occupational segregation by sex tends to belower in the United States than elsewhere, suggesting that U.S. women have greater labor forceattachment and job skills and/or encounter less discrimination in gaining access to traditionallymale jobs (Blau and Kahn, 1996b; OECD, 1999).Nor does it appear that gender-specific policies account for the relatively modest U.S.gender pay ratio. Virtually all OECD and European Community countries had passed equal payand equal opportunity laws by the mid-1980s, but the United States implemented its antidiscrimination legislation before most other countries (Blau and Kahn, 1996b). By internationalstandards, the United States does have a relatively weak entitlement to family leave, consisting ofan unpaid 13-week mandated period, which was only introduced in 1993. In contrast, most22OECD countries have a much longer period of leave, and this leave is usually paid (Ruhm,1998). Some research on the impact of parental leave has found a positive effect of short leaveentitlements on women’s relative wages, although extended leaves have been found to have theopposite effect (Ruhm, 1998; Waldfogel, 1998). Child care is another important area of publicpolicy which particularly affects women, but one which is more difficult to summarize across alarge set of countries. Some available evidence suggests that, as of the mid-1980s, the UnitedStates had a smaller share of young children in publicly funded child care than many other OECDcountries, but provided relatively generous tax relief for child care expenses (Gornick, Myers andRoss, 1997).Since gender-specific factors appear unlikely to account for the mediocre ranking of theU.S. gender earnings ratio, what about more general charactistics of the wage structure? Wageinequality is much higher in the United States than elsewhere. This reflects higher skill pricesand sectoral differentials in the United States, although a more dispersed distribution ofproductivity characteristics also plays a role (Blau and Kahn, 1996a, 1999a, 2000).Institutional factors appear to be important in explaining higher U.S. skill prices andsectoral differentials. More heavily unionized economies in which collective bargaining takesplace at more centralized levels have lower overall wage dispersion, all else equal (Blau andKahn, 1999a). Among the OECD nations, the United States stands at an extreme with anespecially low rate of collective bargaining coverage, pay setting which is often determined at theplant level even within the union sector, and an absence of formal or informal mechanisms toextend union-negotiated pay rates to nonunion workers. Further, minimum wages are lowerrelative to the median in the United States than in most other Western countries (OECD 1998).A significant portion of the male-female pay gap in the United States is associated withinterindustry or interfirm wage differentials that result from its relatively decentralized-paysetting institutions (Blau, 1977; Groshen, 1991; Bayard, Hellerstein, Neumark and Troske, 1999).Thus, centralized systems which reduce the extent of wage variation across industries and firmsare likely to lower the gender differential, all else equal. Moreover, in all countries the female23wage distribution lies below the male distribution. Thus, wage institutions that consciously raiseminimum pay levels, regardless of gender, will tend to lower male-female wage differentials. Ofcourse, these kinds of interventions may also produce labor market problems like unemploymentand inefficiencies in allocating labor.13Table 4 presents some descriptive information that allows us to make an initialdetermination of the relative strength of gender-specific factors and overall wage structure inexplaining the gender pay gap. It is based on our calculations using International Social SurveyProgramme (ISSP) microdata and presents information on the United States and five majorWestern countries for 1985-86 and for 1993-94. These countries are a subset of those included inthe ISSP for which data are available in both the 1980s and 1990s. Our findings were similar,however, when we considered the full set of countries. These two periods allow us to observehow the changing economic environment of the 1980s and 1990s affected women in the UnitedStates compared to those elsewhere. Earnings are corrected for differences in weekly hoursworked.14Our results for the ranking of the U.S. gender wage ratio compared to the non-U.S.average are qualitatively similar to Table 3. We again find that the U.S ratio lagged behind theother countries substantially in the mid-1980s (see top panel, middle column). By 1993-94,however, the United States had closed much of this gap (bottom panel, middle column). Theaverage female percentiles presented in the first column of the table are of interest as an indicatorof gender-specific factors. In 1985-86, the wages of U.S. women ranked at the 31.9 percentile ofthe male wage distribution, virtually the same ranking as the average for the other countries. By1993-94, the percentile ranking of the wages of U.S. women, 36.9, was considerably higher thanthe non-U.S. average ranking of 32.0. The percentile rankings suggest that relative qualificationsand treatment of U.S. women were similar to women in the other countries in the mid-1980s and13. See Blau and Kahn (1999a) for a summary of the evidence on many of the issues concerning labor market flexibility.14. For details on the wage data in the ISSP, see Blau and Kahn (1999b).24actually favored U.S. women by the mid-1990s.Although the percentile rankings are suggestive, in order to determine the relativestrength of gender-specific factors and wage structure, we need to ascertain the wageconsequences of women’s placement in the male wage distribution. The hypothetical gender payratios shown in the last column of Table 4 enable us to do just that. They show what the genderpay ratio would be if men and women in each country had their own relative position in the wagedistribution, but overall wage inequality was at U.S. levels. So, for example, a man or woman atthe 25th percentile of the male wage distribution in Australia would receive a wage equal to amale at the 25th percentile of the U.S. male wage distribution in the same year. For thesehypothetical wage ratios, we find that the U.S. gender ratio is higher than the non-U.S. average ofthe distribution-corrected ratios in both periods: 8.7 percentage points higher in 1985-86 and 13.9percentage points higher in 1993-94. We conclude that, compared to women in the othercountries, U.S. women are better qualified relative to men and/or encounter less discrimination.The mediocre ranking of the U.S. gender ratio in the face of these favorable gender specificfactors is a consequence of the higher level of wage inequality in the United States, which placesa much higher penalty on being below average in the wage distribution.The effect of wage structure can also be seen by comparing the hypothetical gender gapfor each country shown in the third column of Table 4 — where workers are evaluated at theiractual percentile in the wage distribution of their own country but the distribution itself is shiftedto reflect the U.S. level of wage inequality — to its actual gender pay gap as shown in the middlecolumn of the table. In every case, the gender pay ratio would be higher using own country wagedistributions, usually substantially so. On average, the more compressed wage distributions inthese countries increased the gender wage ratio from 55 percent to 72.1 percent in the 1980s (toppanel, sixth row) and from 59 percent to 76.8 percent in the 1990s (bottom panel, penultimaterow).Table 4 also suggest in several ways that the relative qualifications or treatment of U.S.women compared to women in other countries improved between the 1980s and 1990s. First, the25average female percentile in the male wage distribution rose from 31.8 to 36.9 in the UnitedStates, but the average for the other countries was relatively stable (as shown in column 1).Second, the gender pay ratio evaluated at the U.S. male wage distribution rose by 9.2 percentagepoints in the United States, in comparison to a smaller average rise of 4 percentage points in theother countries (as shown in column 3). Finally, the effect of the higher level of U.S. wageinequality was fairly stable: if the other countries had the U.S. male wage structure, the non-U.S.average gender gap would have been increased by 17.1 percentage points in 1985-86 and 17.8percentage points in 1993-94 (comparing columns 2 and 3).15Why did changes in gender-specific factors favor U.S. women relative to those in othercountries during this period? The reasons may be much the same as the factors considered aboveas to why the gender pay gap in the United States narrowed over time. The relative qualificationsand experience of American women may have improved faster than those of women in othercountries. And, if women’s labor force attachment increased more in the United States thanelsewhere, the associated reductions in statistical discrimination against women could well havealso been larger.The data in Table 4 suggest a determining role for wage structure in raising the U.S.gender pay gap relative to that in other countries. However, it is possible to test this relationshipmore directly, as we did in a recent paper (Blau and Kahn 1999b). Using microdata for eachcountry and year from the 1985-94 ISSP data (100 country-year observations in all), we foundstrong evidence that higher inequality of male wages (controlling for the distribution of maleproductivity characteristics) and higher female labor supply had large, statistically significant,15. As noted above, one possible objection to the type of decomposition used in Table 4 is that, under certainassumptions, there could be a mechanical positive correlation between male wage inequality and the average femalepercentile (Suen 1997). But across our full set of countries in the ISSP, there was in fact little statistical relationshipbetween the average female percentile in the male distribution and the standard deviation of the log of male wages,providing evidence against such a mechanical relationship (Blau and Kahn 1999b). Another possible objection tothe decompositions is that they assume that the entire difference in male inequality across countries is due to labormarket prices and rents rather than population heterogeneity. However, in other work (Blau and Kahn 1996a; 2000),we found that higher U.S. prices are in fact an important reason for higher male wage inequality in the U.S., thoughpopulation heterogeneity also plays a role.26positive effects on the gender pay gap. The differences in inequality of male wages werequantitatively more important than female labor supply in explaining differences across countriesin the size of the gap. Based on these regression estimates, the contribution of higher wageinequality and higher female labor supply in the U.S. to the larger U.S. gender pay gap can beestimated. We found that both helped to explain the higher U.S. gap, with wage inequality beingconsiderably more important. Interestingly, these variables were more than sufficient to accountfor the higher U.S. gender pay gap, suggesting that unmeasured factors, perhaps higher femalequalifications or less discrimination, favored U.S. women.16ConclusionOur analysis suggests important roles for both gender-specific factors, including genderdifferences in qualifications and labor market treatment, as well as overall wage structure, theprices the labor market sets for skills and employment in particular sectors, in influencing thesize of the gender pay gap. What do these factors imply about the future of the gender wage gapin the U.S.?The narrowing in the U.S. gender pay gap decelerated in the 1990s and gender-specificfactors seem to be the source of this slowing convergence. Without a more detailed analysis ofthe trends in the pay gap over this period than currently available data permit, it is not possible toknow which particular gender-specific factors account for this. It is also difficult to say whetherthis represents merely a pause in the continued closing of the gender pay gap or a more long-termstalling of this trend. With respect to wage structure, there appears to have been a deceleration inthe trend towards rising inequality over the 1990s. To the extent this continues, a major factor16. It could be argued that the gender pay gap itself could affect male wage inequality and female net supply. On theformer effect, see Fortin and Lemieux (1998) discussed above. Recognizing that the explanatory variables may beendogenous, we estimated reduced form models in which male wage inequality and female net supply were replaced byinstitutional variables such as collective bargaining coverage. We found that more highly unionized countries had muchsmaller gender pay gaps, all else equal, an effect that is consistent with the estimated positive effect of wage inequalityon the gender pay gap.27retarding convergence in the gender gap will be diminished.Taking these factors together, it seems plausible that the gender pay gap will continue todecline at least modestly in the next few years. But it seems unlikely to vanish. Women continueto confront discrimination in the labor market, although its extent seems to be decreasing.In addition, at least some of the remaining pay gap is surely tied to the gender division oflabor in the home, both directly through its effect on women’s labor force attachment andindirectly through its impact on the strength of statistical discrimination against women. Womenstill retain primary responsibility for housework and child care in most American families.However, this pattern has been changing as families respond to rising labor market opportunitiesfor women that increase the opportunity cost of such arrangements. Further, policies thatfacilitate the integration of work and family responsibilities, both voluntary and governmentmandated, have become increasingly prevalent in recent years. Employers are likely to continueto expand such policies as they respond to the shifting composition of the work force and a desireto retain employees in whom they have made substantial investments. In the longer run, theincreasing availability of such policies will make it easier for women to combine work andfamily, and also for men to take on a greater share of household tasks.28ReferencesAigner, Dennis and Glen Cain. 1977. “Statistical Theories of Discrimination in LaborMarkets.” Industrial and Labor Relations Review. 30:2, pp. 175-87.Barron, John M., Dan A. Black, and Mark A. Lowenstein. 1993. “Gender Differences inTraining, Capital and Wages.” Journal of Human Resources. 28:2, pp. 342-64.Bayard, Kimberly, Judith Hellerstein, David Neumark, and Kenneth Troske. 1999. “NewEvidence on Sex Segregation and Sex Difference in Wages From Matched Employee-EmployerData.” NBER Working Paper No. 7003.Becker, Gary S. 1957. The Economics of Discrimination. Chicago: University of ChicagoPress.Becker, Gary S. 1985. “Human Capital, Effort, and the Sexual Division Labor.” Journal ofLabor Economics. 3:1 Supp., pp. S33-S58.Bergmann, Barbara. 1974. “Occupational Segregation, Wages, and Profits When EmployersDiscriminate by Race or Sex.” Eastern Economic Journal. 1:1-2, pp. 103-10.Berman, Eli, John Bound, and Zvi Griliches. 1994. “Changes in the Demand of SkilledLabor Within U.S. Manufacturing Industries: Evidence From the Annual Survey ofManufacturing.” Quarterly Journal of Economics. 109:2, pp. 367-97.Bertrand, Marianne and Kevin F. Hallock. 1999. “Gender Compensation DifferentialsAmong U.S. High-Level Executives.” Working Paper, Princeton and University of Illinois.Black, Sandra E. and Philip E. Strahan. 1999. “Rent-Sharing and Discrimination: TheEffects of Deregulation on the Labor Market.” Working Paper.Blau, Francine D. 1977. Equal Pay in the Office. Lexington, MA: Lexington Books.Blau, Francine D. 1998. “Trends in the Well-Being of American Women, 1970-1995.” Journalof Economic Literature. 36:1, pp. 112-65.29Blau, Francine D., Marianne A. Ferber, and Anne E. Winkler. 1998. The Economics ofWomen, Men, and Work. 3rd ed. Englewood Cliffs, NJ: Prentice-Hall.Blau, Francine D. and Lawrence M. Kahn. 1996a. “International Differences in Male WageInequality: Institutions Versus Market Forces.” Journal of Political Economy. 104:4, pp. 791-837.Blau, Francine D. and Lawrence M. Kahn. 1996b. “Wage Structure and Gender EarningsDifferentials: an International Comparison.” Economica. 63 :Supp., pp. S29-S62.Blau, Francine D. and Lawrence M. Kahn. 1997. “Swimming Upstream: Trends in theGender Wage Differential in the 1980s.” Journal of Labor Economics. 15:1 pt. 1, pp. 1-42.Blau, Francine D. and Lawrence M. Kahn. 1999a. “Institutions and Laws in the LaborMarket,” in Handbook of Labor Economics, vol. 3A, Orley C. Ashenfelter and David Card, eds.Amsterdam: Elsevier, pp. 1399-461.Blau, Francine D. and Lawrence M. Kahn. 1999b. “Understanding International Differencesin the Gender Pay Gap.” Working Paper, Cornell University.Blau, Francine D. and Lawrence M. Kahn. 2000. “Do Cognitive Test Scores Explain HigherU.S. Wage Inequality?” Working Paper, Cornell University.Blau, Francine D., Patricia Simpson, and Deborah Anderson. 1998. “Continuing Progress?Trends in Occupational Segregation in the United States Over the 1970s and 1980s.” FeministEconomics. 4:3, pp. 29-71.Brown, Charles and Mary Corcoran. 1997. “Sex-Based Differences in School Content andthe Male/Female Wage Gap.” Journal of Labor Economics. 15:3, pp. 431-65.Bureau of National Affairs (BNA). 1990. Daily Labor Report, no. 235, December 6, pp. A11-A13 and F1-F10.Cobb-Clark, Deborah A. and Yvonne Dunlop. 1999. “The Role of Gender in JobPromotions.” Monthly Labor Review. 122:12, pp. 32-38.30Costa, Dora L. 2000. “From Mill Town to Board Room: The Rise of Women’s Paid Labor.”Journal of Economic Perspectives. 14:4.England, Paula. 1982. “The Failure of Human Capital Theory to Explain Occupational SexSegregation.” Journal of Human Resources. 17:3, pp. 358-70.Flyer, Frederick and Sherwin Rosen. 1994. “The New Economics of Teachers andEducation.” National Bureau of Economic Research Working Paper No. 4828, August.Federal Human Resources Week (FEDHR). 2000. 6:47, April 5.Fortin, Nicole M. and Thomas Lemieux. 1998. “Rank Regressions, Wage Distributions, andthe Gender Gap.” Journal of Human Resources. 33:3, pp. 610-643.Fuchs, Victor. 1971. “Differences in Hourly Earnings Between Men and Women.” MonthlyLabor Review. 94:5, pp. 9-15.Furchtgott-Roth, Diana and Christine Stolba. 1999. Women’s Figures: an Illustrated Guideto the Economic Progress of Women in America. Washington, D.C.: The AEI Press.Glass Ceiling Commission. 1995. “A Solid Investment: Making Full Use of the Nation’sHuman Capital.” Recommendations of the Glass Ceiling Commission, Washington DC.Goldin, Claudia. Understanding the Gender Gap: An Economic History of American Women.Oxford: Oxford University Press, 1990.Goldin, Claudia and Cecilia Rouse. forthcoming. “Orchestrating Impartiality: the Impact of‘Blind’ Auditions on Female Musicians.” American Economic Review.Gornick, Janet C., Marcia K. Meyers, and Katherin E. Ross. 1997. “Supporting theEmployment of Mothers: Policy Variation Across Fourteen Welfare States.” Journal ofEuropean Social Policy. 7:1, pp. 45-70.Groshen, Erica L. 1991. “The Structure of the Female/Male Wage Differential: Is It Who YouAre, What You Do, or Where You Work?” Journal of Human Resources. 26:3, pp. 457-72.31Gunderson, Morley. 1989. “Male-Female Wage Differentials and Policy Responses.” Journalof Economic Literature. 27:1, pp. 46-72.Hellerstein, Judith K., David Neumark, and Kenneth Troske. 1997. “Market Forces and SexDiscrimination.” National Bureau of Economic Research Working Paper 6321.Hersch, Joni and W. K. Viscusi. 1996. “Gender Differences in Promotions and Wages.”Industrial Relations. 35:4, pp. 461-72.Jacobs, Jerry A. 1999. “The Sex Segregation of Occupations: Prospects for the 21st Century,”in Handbook of Gender in Organizations, Gary N. Powell, ed. Newbury Park, CA: SagePublications, pp. 125-41.Juhn, Chinhui, Kevin M. Murphy, and Brooks Pierce. 1991. “Accounting for the Slowdownin Black-White Wage Convergence,” in Workers and Their Wages, Marvin Kosters, Ed.Washington, D.C.: AEI Press, pp. 107-43.Katz, Lawrence F. and David H. Autor. 1999. “Changes in the Wage Sructure and EarningsInequality,” in Handbook of Labor Economics, vol. 3A, Orley C. Ashenfelter and David Card,eds. Amsterdam: Elsevier, pp. 1463-555.King, Ronette. 1997. “Women Taking Action Against Many Companies.” The TimesPicayune, April 27.Krueger, Alan B. 1993. “How Computers Have Changed the Wage Structure: Evidence fromMicrodata,1984-1989.” Quarterly Journal of Economics. 108:1, pp. 33-60.Lewin, Tamar. 1990. “Partnership Awarded to Woman in Sex Bias Case.” The New YorkTimes, May 16, pp. A1, A12.Leonard, Jonathan. 1989. “Women and Affirmative Action.” Journal of EconomicPerspectives. 3:1, pp. 61-75.MacPherson, David A. and Barry T. Hirsch. 1995. “Wages and Gender Composition: WhyDo Women’s Jobs Pay Less?” Journal of Labor Economics. 13:3, pp. 426-71.32Massachusetts Institute of Technology. 1999. “A Study on the Status of Women Faculty inScience at MIT.” .McCue, Kristin. 1996. “Promotions and Wage Growth.” Journal of Labor Economics. 14:2,pp. 175-209.McDowell, John M., Larry D. Singell Jr., and James P. Ziliak. 1999. “Cracks in the GlassCeiling: Gender and Promotion in the Economics Profession.” American Economic Review. 89:2,pp. 392-96.Meyer, Bruce D. and Dan T. Rosenbaum. 1999. “Welfare, the Earned Income Tax Credit, andthe Labor Supply of Single Mothers.” NBER Working Paper No. 7363.Mincer, Jacob and Solomon Polachek. 1974. “Family Investments in Human Capital:Earnings of Women.” Journal of Political Economy. 82:2 pt. 2, pp. S76-S108.Neumark, David M. 1996. “Sex Discrimination in Restaurant Hiring: an Audit Study.”Quarterly Journal of Economics. 111:3, pp. 915-41.O’Neill, June and Solomon Polachek. 1993. “Why the Gender Gap in Wages Narrowed in the1980s.” Journal of Labor Economics. 11:1 pt. 1, pp. 205-28.OECD. 1998. Employment Outlook. Paris: OECD.OECD. 1999. Employment Outlook. Paris: OECD.Reskin, Barbara F. and Heidi I. Hartmann, eds. 1986. Women’s Work, Men’s Work: SexSegregation on the Job. Washington D.C.: National Academy Press.Royalty, Anne B. 1996. “The Effects of Job Turnover on the Training of Men and Women.”Industrial and Labor Relations Review. 49:3, pp. 506-21.Ruhm, Christopher J. 1998. “The Economic Consequences of Parental Leave Mandates:Lessons From Europe.” Quarterly Journal of Economics. 113:1, pp. 285-317.33Sorenson, Elaine. 1990. “The Crowding Hypothesis and Comparable Worth Issue.” Journal ofHuman Resources. 25:1, pp. 55-89.Suen, Wing. 1997. “Decomposing Wage Residuals: Unmeasured Skill or Statistical Artifact?”Journal of Labor Economics. 15:3, pt. 1, pp. 555-66.Waldfogel, Jane. 1998. “Understanding the ‘Family Gap’ in Pay for Women with Children.”Journal of Economic Perspectives. 12:1, pp.157-170.Weinberg, Bruce. 2000. “Computer Use and the Demand for Female Workers.” Industrial andLabor Relations Review. 53:2, pp. 290-308.Weinberger, Catherine J. 1998. “Race and Gender Wage Gaps in the Market for RecentCollege Graduates.” Industrial Relations. 37:1, pp. 67-84.Wood, Robert G., Mary E. Corcoran, and Paul Courant. 1993. “Pay Differences Among theHighly Paid: the Male-Female Earnings Gap in Lawyers’ Salaries.” Journal of Labor Economics.11:3, pp. 417-41.34Figure 1 Female-to-Male Earnings Ratios of Full-Time Workers, 1955-19995055606570758085909510055 60 65 70 75 80 85 90 95YearEarnings ratio (percent)AnnualWeekly35Table 1Female/Male Hourly Wage Ratios of Full-Time Workersby Age, 1978-98A. Wage Ratios 1978 1988 199818-24 0.824 0.930 0.94225-34 0.703 0.828 0.85035-44 0.589 0.687 0.76145-54 0.582 0.647 0.71655-64 0.623 0.610 0.693B. Changes 1978-88 1988-98Between cohorts18-24 0.105 0.01225-34 0.125 0.02335-44 0.098 0.07445-54 0.066 0.06855-64 -0.012 0.082Within cohorts18-24 -0.024 -0.09225-34 -0.016 -0.06735-44 0.058 0.02945-54 0.029 0.045Notes: Gender ratios are computed as exp(ln Wf – lnWm),where ln Wf and ln Wm are female and male average logwages.Source: Authors’ tabulations from the Current PopulationSurveys.36Table 2Impact of Widening Wage Inequality on Trends in the Female-Male Wage Ratio ofFull-Time Workers, 1978-98 (1998 Dollars)Change1978 1988 1998 1978-88 1988-98 1978-98MalesWage $14.06 $14.21 $14.96 $0.15 $0.75 $0.89Ln (wage) 2.643 2.654 2.705 0.010 0.051 0.062(Std dev) (0.527) (0.594) (0.609) 0.067 0.015 0.082FemalesWage $9.21 $10.52 $11.70 $1.31 $1.18 $2.49Ln (wage) 2.220 2.354 2.460 0.133 0.106 0.239(Std dev) (0.436) (0.511) (0.547) 0.075 0.036 0.111Mean female percentilein male distribution 26.02 34.76 38.48 8.74 3.71 12.46Gender RatioActual 0.655 0.741 0.782 0.086 0.042 0.127Fixed Weight Average (1978 Base) 0.655 0.726 0.763 0.071 0.037 0.108Fixed Distribution (1978 Base) 0.655 0.766 0.807 0.111 0.041 0.152Notes: See Table 1 for the definition of the gender wage ratios.Source: Authors’ tabulations from the Current Population Survey.37Table 3Female/Male Ratios, Median Weekly Earnings of Full-time WorkersChange 1979-81Country 1979-81 1989-90 1994-98 to 1994-98 AustraliaAustriaBelgiumCanadaFinlandFrance (net)GermanyIrelandItalyJapanNetherlandsNew ZealandSpainSwedenSwitzerlandUnited KingdomUnited StatesNon-US Average1979-81 samplefull sample0.8000.649na0.6330.7340.7990.717nana0.587na0.734na0.838na0.6260.6250.8140.6740.8400.6630.7640.8470.737na0.8050.5900.7500.759na0.7880.7360.6770.7060.8680.6920.9010.6980.7990.8990.7550.7450.8330.6360.7690.8140.7110.8350.7520.7490.7630.0680.043na0.0650.0650.1000.038nana0.049na0.080na-0.003na0.1230.1380.7120.7120.7310.7460.7740.7780.0630.067 Notes: The years covered for each country are as follows: Australia: 79,89,98;Austria: 80,89,94; Belgium: 89,95; Canada: 81, average of 88 & 90, 94; France:79,89,96; W. Germany: 84,89,95; Italy: 89,96; Japan: 79,89,97; Netherlands:90,95; New Zealand: average of 88 & 90, 97; Sweden: average of 78 & 80, 89,96; Switzerland: 91, 96; United Kingdom: 79,89,98; United States: 79, 89, 96.Source: Authors’ calculations from unpublished OECD data.38Table 4Female Wages Relative to the Male Distribution, Actual and Wage DistributionCorrected Gender Wage Ratios, 1985-86 and 1993-94 Average FemaleFemale/Male WagePercentile in MaleActual Female/MaleRatio at US MaleWage DistributionWage RatioWage Distribution 1985-86 AustraliaW GermanyBritainAustriaItalyNon-US AverageUnited States33.428.425.831.040.531.831.90.7160.7020.6600.7180.8080.7210.6370.5550.5360.4710.5150.6720.5500.637 1993-94 AustraliaW GermanyBritainAustriaItalyNon-US AverageUnited States34.721.535.133.335.232.036.90.7730.6930.7820.7970.7950.7680.7290.6670.3680.6890.6050.6220.5900.729 Notes: The years covered for each country are as follows: Australia (86, 94); West Germany(85-86, 93); Britain (85-86; 93-94); USA (85-86; 93-94); Austria (85-6, 94); Italy (86, 93-94).Earnings are corrected for weekly hours differences. See Blau and Kahn (1999b) for details.Source: Authors’ calculations from International Social Survey Programme (ISSP) microdata.