Job Mobility and Early Career Wage Growth of White, African-American, and Hispanic Women n Sigal Alon, Tel-Aviv University Marta Tienda, Princeton University Objective. This article examines whether and how young women’s job mobility influences racial and ethnic wage-growth differentials during the first eight years after leaving school. Methods. We use the NLSY-79 Work History File to simulate the influence of job mobility on the wages of skilled and unskilled workers. Re- sults. African-American and Hispanic women average less job mobility than white women, especially if they did not attend college. Unskilled women who experience frequent job changes during the first four postschool years reap positive wage returns, but turnover beyond the shopping period incurs wage penalties. Job mo- bility does not appear to boost wage growth for college-educated women. Con- clusions. Among unskilled women, race and ethnic wage disparities partly derive from group differences in the frequency of job changes, but unequal returns to job mobility drive the wage gaps for skilled women. We discuss several explanations for these disparities. Based on narrowing wage gaps among women of color and whites during the early to mid 1970s, researchers inferred a declining significance of race for women’s economic fortunes (England and Browne, 1992). However, more recent indicators reveal appreciable wage disparities between minority and white women (Browne, 1998; Bound and Dresser, 1998; Blau, 1998). Although white women’s wages have risen steadily since 1980, African- American women experienced little wage growth and Hispanic women fared even worse (Altonji and Blank, 1999). There is general consensus that large racial and ethnic disparities in educational attainment during a period of rising returns to skill are primarily responsible for increased wage disparities among women (Bound and Dresser, 1998; Anderson and Shapiro, 1996; Blau and Kahn, 1997). Racial differences in the accumulation of work n Direct correspondence to Sigal Alon, Department of Sociology and Anthropology, Tel Aviv University, Tel Aviv, Ramat Aviv, Tel Aviv 69978, Israel h [email protected]i . Sigal Alon will share all data and coding information with those wishing to replicate the study. This research was supported by grants from the National Science Foundation (SBR- 9601995) and the W.T. Grant Foundation to Princeton University. The authors gratefully acknowledge the Princeton University Office of Population Research and the Department of Sociology for generous institutional support. SOCIAL SCIENCE QUARTERLY, Supplement to Volume 86 r2005 by the Southwestern Social Science Association
Transcript
Job Mobility and Early Career WageGrowth of White, African-American, andHispanic Womenn
Sigal Alon, Tel-Aviv University
Marta Tienda, Princeton University
Objective. This article examines whether and how young women’s job mobilityinfluences racial and ethnic wage-growth differentials during the first eight yearsafter leaving school. Methods. We use the NLSY-79 Work History File to simulatethe influence of job mobility on the wages of skilled and unskilled workers. Re-sults. African-American and Hispanic women average less job mobility than whitewomen, especially if they did not attend college. Unskilled women who experiencefrequent job changes during the first four postschool years reap positive wagereturns, but turnover beyond the shopping period incurs wage penalties. Job mo-bility does not appear to boost wage growth for college-educated women. Con-clusions. Among unskilled women, race and ethnic wage disparities partly derivefrom group differences in the frequency of job changes, but unequal returns to jobmobility drive the wage gaps for skilled women. We discuss several explanations forthese disparities.
Based on narrowing wage gaps among women of color and whites duringthe early to mid 1970s, researchers inferred a declining significance of racefor women’s economic fortunes (England and Browne, 1992). However,more recent indicators reveal appreciable wage disparities between minorityand white women (Browne, 1998; Bound and Dresser, 1998; Blau, 1998).Although white women’s wages have risen steadily since 1980, African-American women experienced little wage growth and Hispanic women faredeven worse (Altonji and Blank, 1999). There is general consensus that largeracial and ethnic disparities in educational attainment during a period ofrising returns to skill are primarily responsible for increased wage disparitiesamong women (Bound and Dresser, 1998; Anderson and Shapiro, 1996;Blau and Kahn, 1997). Racial differences in the accumulation of work
nDirect correspondence to Sigal Alon, Department of Sociology and Anthropology, TelAviv University, Tel Aviv, Ramat Aviv, Tel Aviv 69978, Israel [email protected]. SigalAlon will share all data and coding information with those wishing to replicate the study.This research was supported by grants from the National Science Foundation (SBR-9601995) and the W.T. Grant Foundation to Princeton University. The authors gratefullyacknowledge the Princeton University Office of Population Research and the Department ofSociology for generous institutional support.
SOCIAL SCIENCE QUARTERLY, Supplement to Volume 86r2005 by the Southwestern Social Science Association
experience also contributed to the widened black-white earnings gap(McCrate and Leete, 1994), but there is no evidence whether and how muchjob mobility contributed to the growing wage disparities.
Because models of job change extend conventional human capital expla-nations about how much earnings rise with experience, they can potentiallyaccount for some of the differences in wage growth. For example, Topel andWard (1992) relate men’s intense job shopping to early career wage growthby showing that wage gains for job changes account for at least a third ofearly career wage growth. Very few studies examine racial differences inmen’s wage gains from job mobility (cf. Oettinger, 1996), and correspond-ing evidence for women is more limited. Therefore, we know little abouthow job mobility shapes the market prospects of African-American andHispanic women (Altonji and Blank, 1999; Browne, 1998). Accordingly, weassess whether and how much women’s job transitions account for racial andethnic wage-growth differentials during the first eight years after schoolleaving, which is the critical time for launching labor market careers.
To our knowledge, there is no empirical evidence that ties racial differencesin women’s job mobility—specifically the timing and frequency of job-to-jobtransitions—to early career wage disparities. Of course, educational attain-ment is important for understanding how job turnover influences women’swages because skilled women change jobs more frequently than their un-skilled counterparts (Royalty, 1998; Holzer and LaLonde, 1999). Moreover,because African-American, white, and Hispanic women differ in both theirschool attainment and their labor market attachment, the analytical challengeis to determine whether the influence of job mobility on wages, if it exists,operates differently for women of color, net of other wage-enhancing factors.
Our analysis of women’s job mobility and wage growth seeks answers totwo questions: (1) Are there differences in the pattern of job mobility, thatis, timing and frequency, between minority and nonminority women withcomparable levels of education and market activity? (2) Are the returns tojob changing uniform among minority and nonminority women withcomparable levels of education and market attachment?
We use data from the NLSY Work History File to analyze the divergingwage trajectories of white, African-American, and Hispanic women by ac-counting for their job-to-job mobility during the first eight years post-schooling. We define job-to-job mobility as any transition between oneemployer and another that involves no more than two months of unem-ployment during the interim.1 An important aspect of women’s work historythat influences wage trajectories is the time spent employed in each post-schooling year. Following Light and Ureta (1990), we compare the impact ofjob mobility on the wages of African-American, white, and Hispanic women
1We focus on the job-to-job transitions because they are directly related to the process ofjob matching while job-to-nonemployment transitions (i.e., exits) reflect employment dis-continuity (Royalty, 1998; Holzer and LaLonde, 1999).
Job Mobility and Early Career Wage Growth of Women 1197
who have accumulated similar amounts of labor force experience. This strat-egy permits an assessment of the wage effect of job changing, independentof racial and ethnic differences in labor force attachment, and the impact ofjob mobility on a set of (relatively) continuously employed women.
The next section briefly reviews the extant literature on women’s jobmobility in the context of rising wage inequality to highlight the importanceof both skill and experience differences in turnover rates. Following a de-scription of data and operational measures, we show the widening wage gapbetween minority and nonminority women and group variation in accu-mulated labor market experience. The multivariate analysis, which estimatesthe effect of job mobility on ln(wage) growth eight years after school de-parture, is used to discern whether and how much the returns to mobilitydiffer according to the timing and frequency of job changes. The resultssuggest that for unskilled women, the positive impact on wages of job mo-bility increases with labor force attachment: continuously employed womenreap the highest returns for job changing during the first four postschoolingyears. However, continued job changing five to eight years after leavingschool incurs wage penalties. There is no evidence that job mobility boostswage growth for college-educated women. We also find significant groupdifferences in both the pattern and the returns to job mobility by skill level.
Literature Review
Job search theories link turnover with wages because the early labor mar-ket years are a period of rapid wage growth as well as extensive job ‘‘shop-ping’’ (Blumen, Kogan, and McCarthy, 1955; Burdett, 1978; Jovanovic,1979a, 1979b). The basic turnover model posits that during the early career,job changes occur because workers receive new information about theircurrent market arrangement or learn about a more attractive alternativematch ( Jovanovic, 1979a, 1979b). Theoretically, it is interesting to knowwhether job changes occur because of information about the currentmatch—the model of ‘‘experience good’’—(Johnson, 1978; Jovanovic,1979a) or about an alternative match—the model of ‘‘search good’’—(Burdett, 1978; Jovanovic, 1979b), but wage growth is the expected out-come for both scenarios. Moreover, both ‘‘experience’’ and ‘‘search’’ modelspredict that job mobility declines with time, albeit for different reasons.
The empirical literature on the relationship between job mobility andwage growth has produced equivocal results, particularly for women. In ahighly influential paper, Topel and Ward (1992) show that for young whitemen, job mobility exerts a large positive influence on wage growth. Theyattribute over one-third of men’s average wage growth during their firstdecade of market activity to job shopping. Loprest (1992) reaches a similarconclusion for men, but not for young women, although others claim thatwomen benefit from job mobility as much as men do (Keith and
1198 Social Science Quarterly
McWilliams, 1997; Abbott and Beach, 1994). Building on these insights, wehypothesize that if job mobility is an important wage-growth mechanismduring women’s early labor market careers, it could potentially explainwidened racial and ethnic gaps that stem either from differences in the levelof job-to-job mobility or in the returns to these transitions, or both.
There are several reasons why African-American and Hispanic women mayexperience less job-to-job mobility than whites. First, because African-Amer-ican and Hispanic women’s employment rates are lower than those of whites,they spend less time in the market. Put simply, the less time spent working,the lower the ‘‘risk’’ of job-to-job mobility. Furthermore, workers with stronglabor force attachment may engage in more job shopping because they standto gain more from locating more attractive jobs (Barron, Black, and Loe-wenstein, 1993). Second are racial and ethnic differences in educational at-tainment (Mare, 1995.) By increasing workers’ market options andopportunity costs, educational attainment may increase job mobility inde-pendent of the fact that highly-skilled women are also more committed tomarket activity than unskilled women (Johnson, 1979; Weiss, 1984; Royalty,1998). Third, minority workers may face greater constraints in accessing de-sirable jobs for which they are qualified. Oettinger (1996) argues that AfricanAmericans face greater uncertainty about productivity than do whites, henceeven if no wage gap exists at the time of labor force entry, one will develop asworkers accumulate labor force experience. He finds no racial wage gap atlabor force entry, but documents widened wage disparities owing to higherreturns to job mobility for white compared with African-American men.
Fourth, women of color likely receive fewer job offers, lower quality jobopportunities, and lower wage offers than white women owing to slack labormarket conditions, weak social networks, statistical discrimination, or all ofthe above. Minority women may experience less job turnover because, morethan whites, they have imperfect information about ‘‘good’’ job vacancies,and because they lack the networks conducive to quality worker-employermatches (Alon and Stier, 1996; Wilson, 1987; Sullivan, 1989). Residentialsegregation and concentration in local labor markets that offer limited em-ployment opportunities can further constrain minority women’s job mo-bility, especially for unskilled workers (Browne, 1998). Lastly, minoritywomen may experience lower levels of job turnover because they have higherreservation wages than comparably-skilled white women. Although Stier andTienda (2001) found no evidence that inner-city minority women’s reser-vation wages were higher than their white counterparts, it is conceivable thatfamily circumstances that increase women’s economic uncertainty, such asmarital status, teen motherhood, or a partner with low market capacity, mayinhibit their willingness to leave a secure job (Stier and Tienda, 2001).
As mentioned, we assess the wage effect of job mobility, independent ofthe influence of labor force attachment. In addition, our analysis addressestwo other issues, raised in the foregoing review, that may shape the linkbetween mobility and wages. First is the level of educational attainment.
Job Mobility and Early Career Wage Growth of Women 1199
The inability of less-educated women to keep up with their highly-skilledcounterparts (owing to reduced demand for unskilled labor) requires eval-uating the returns to mobility by education strata (Bound and Freeman,1992; Juhn, 1992, 1997; Levy and Murnane, 1992; Holzer, 1996). Forexample, Royalty (1998) traces most of the sex differences in the level of jobmobility to differences between women lacking any college education and allothers. The second issue that we consider is the timing and frequency of jobmobility. Light and Ureta (1995) and Light and McGarry (1998) demon-strate the importance of the timing and pattern accumulated experience inaccounting for wage dispersion. Their work underscores the importance ofmaking temporal refinements in the measurement of employment transitionsto determine whether and how much job mobility influences wage growth. Ifturnover rates decline as workers mature, we would expect the theorizedpositive effect of job mobility to be restricted to the initial years after leavingschool, and to a moderate number of transitions overall. Presumably, fre-quent transitions that occur shortly after school departure are part of careerbuilding geared to economic mobility. However, women who experiencefrequent employer changes well after the job-matching process has beencompleted could incur wage penalties if their job-specific tenure is reduced.
Data
Sample
We analyze the National Longitudinal Survey of Youth (NLSY ), a na-tional probability sample of 12,686 individuals ages 14–21 as of January 1,1979, who were reinterviewed annually until 1994. We restricted our sam-ple to women (dropping 6,403 men), excluding the nonrandom militaryand poverty samples. Randomly drawn oversamples of African-Americanand Hispanic youth are included to maximize sample sizes for tabularcomparisons with white youth. Many respondents, especially those ages 18–21 at the first interview, had held one or more jobs that were not accuratelyreported in the survey. Therefore, we restrict the sample to women who wereages 13–16 as of 1978 in order to minimize problems caused by left cen-soring of labor force participation (dropping 2,346 women). We also delete28 women who did not work a single month between ages 16 and 30, andhence were never at risk of experiencing a job transition. Missing data in 741work histories reduced the sample to 1,780 young women whose school andwork careers are observed for 15 years.
The analysis classifies each respondent into four education categories indi-cating the highest level completed (HS dropout, HS graduate, some college, andcollege graduate). All measures of work experience—job mobility and percent oftime spent in the labor force—are measured for a window of eight yearsfollowing school departure using the median age for a given schooling category
1200 Social Science Quarterly
(17, 18, 20, and 23, respectively) to begin the interval.2 Only women with validwage information for both the first and eighth year after school leaving wereeligible for the analysis.3 The final sample includes 1,320 women with validwage information: 701 whites, 365 African Americans, and 254 Hispanics. Allanalyses are weighted to adjust for oversampling, nonresponse, and attrition.
Data Construction
The NLSY Work History File reports weekly employment status for eachrespondent, which we use to construct a monthly history of primary em-ployment status based on the job in which respondents worked the mosthours per month. That respondents average 200 person-months in theirwork history records enables precise tracking of all employment transitionsfrom ages 16 to 30. For each month we constructed a measure indicatingwhether the respondent was employed. Working women’s main job wasderived by counting the number of employers and identifying the job withthe most hours worked (in case of dual job holding).
Work History Measures
The job mobility measure (job-to-job transition) is constructed by countingall transitions involving moves from one employer to another for the first eightpostschool years (T1–T8), with no more than two nonemployment monthsseparating the jobs. The percent of time spent employed is the number of em-ployed months divided by the total number of months in each year times 100.Pooled measures were computed for the first (T1–T4) and second (T5–T8)parts of the eight-year observation window. Finally, to compute hourly wages,we summed nominal hourly wages for all person-months and divided them bythe number of nonmissing months with wage information. This approachyields reasonably precise average annual hourly wages for each postschool year.
Control Variables
The statistical models include controls for several covariates known toinfluence wage growth. Appendix A provides a detailed definition of allvariables and descriptive statistics.
2We use median age for a given schooling category and not the actual date of schooldeparture because of unreliable enrollment data, including missing data problem and illogicaltrajectories.
3To minimize missing data, we also included 180 cases that lacked either the first or theeighth year of wage data, but had valid wage data for the second or the ninth postschoolingyears. This strategy retains the eight-year observation window for these observations.
Job Mobility and Early Career Wage Growth of Women 1201
Results
Figure 1, which displays year-specific average hourly wages separately forAfrican-American, white, and Hispanic women, concurs with Oettinger’s(1996) findings for men, showing a widening wage gap as they accumulateworkforce experience. White women average $5.07 when they leave school,compared with $4.15 and $4.59, respectively, for African-American andHispanic women. Eight years later, white women’s hourly wages rise to$9.91, but Hispanic women earn $1 less and African-American women $2less on an average hourly basis. The racial gap at T8 implies an annualearnings deficit of $4,000.
To assess whether and how much increased wage gaps reflect group dif-ferences in skills, we conducted diagnostic analyses of wage differentials byeducation levels. Results showed race and ethnic differences in wage growthfor every educational level. Moreover, African-American wage growth issignificantly lower than that of whites (and Hispanics) only among thosewho did not continue their education beyond high school. Because racialand ethnic wage-growth disparities only differ among less-skilled women(with high school or less education) but not for skilled women (those withsome college or college degrees), we conduct the statistical analysis separatelyfor these two education strata.
Table 1 illustrates group differences in labor force attachment by skill levelfor the eight-year observation period. There is much more dispersion inlabor force attachment among unskilled compared with skilled women.Unskilled African-American women worked less than 60 percent of the timeduring the eight-year observation window, but their college-educated racial
01 2 3 4 5 6 7 8
2
4
6
8
10
12
Postschooling years
Ave
rag
e h
ou
rly
wag
es
Hispanic
African
WhiteAmerican
FIGURE 1
Average Hourly Wages in First Eight Postschooling Years, All Women (N 5 1,320)
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counterparts worked almost 83 percent of the time, as did skilled Hispanicwomen. Among unskilled women, there is more dispersion in job-to-jobtransitions and differences between groups are statistically significant. Un-skilled white women average 3.3 job transitions—quite similar to theirskilled counterparts—but African-American and Hispanic women average2.2 and 2.7 job changes, respectively. However, college-educated women,who average about three job changes during their early career, exhibit trivialracial and ethnic differences in turnover. These group differences in job-to-job transitions clarify Royalty’s (1998) finding that less-educated womenhave lower turnover relative to more-educated women (and men) by showingthat this difference derives mainly from the behavior of unskilled minorities.
If job mobility contributes to women’s wage growth during their career-launching period, then the observed racial and ethnic differences in the levelof job mobility could accentuate wage dispersion, especially among unskilledwomen. The job search literature postulates, and the empirical literaturedemonstrates, that the greatest benefits of job shopping occur early afterleaving school, but diminish thereafter. Theoretically, early job shoppinginvolves wage mobility as the worker-job match is perfected, whereas pro-longed shopping may reflect churning that undermines job tenure and in-curs wage penalties. Data presented in Table 1 suggest that these relation-ships are not likely to be uniform among demographic and skill groups.
TABLE 1
Cumulative Work Experience During the First Eight Years Following SchoolDeparture by Skill Levela
Total White African American Hispanic
Unskilled Women% time in LF (mean) 72.8 75.4 58.3b,d 67.7c
a% time spent in LF 5 number of employed months out of the total number of months in eachyear multiplied by 100. # of job-to-job transitions 5 job-to-job transitions with the maximum oftwo nonemployment months in between.
bWhite-black difference is significant at po0.05 level.cWhite-Hispanic difference is significant at po0.05 level.dBlack-Hispanic difference is significant at po0.05 level.
Job Mobility and Early Career Wage Growth of Women 1203
Disaggregating the timing and frequency of job transitions illustrates howthe differences in the mean frequency of job mobility depicted in Table 1were generated, and whether there are racial and ethnic differences in thetiming of job changes.4 To consider whether the wage impacts of job-to-jobtransitions are linear—a few job transitions may enhance income prospectswhile numerous job changes may be detrimental to income prospects—forboth periods the number of transitions are recorded in three categories: zero,one to two, and three or more.5
One key insight is that racial and ethnic differences in job mobility arisebecause minorities are not ‘‘movers’’—either they stay with the same em-ployer or they remain jobless for prolonged periods. During the first fouryears after leaving school, only 24 percent of white women experience no jobtransitions compared with 45 and 39 percent of unskilled African Americansand Hispanics, respectively, and 28 to 33 percent, respectively, for skilledminority women. Furthermore, about one in three white women make threeor more job changes within four years of leaving school, but only 16 and 26percent of unskilled African-American and Hispanic women do so, respec-tively, as do 27 and 24 percent of their skilled counterparts.
TABLE 2
Young Women’s Job-to-Job Transitions During the First Eight PostschoolingYears, by Race and Skill Levela
aPercentage of women who experienced each number of job-to-job transitions in thedesignated period.
4Theoretically, averaging the mobility rate of two groups—movers and stayers—couldhave generated white women’s higher level of mobility if the movers experience unusuallyhigh rate mobility. Alternatively, it is possible that a large share of white women engages in amoderate number of job changes. These are important considerations because they aredirectly related to the possible impact of job-to-job transitions on wages and can potentiallyclarify racial/ethnic differences in job mobility patterns.
5We devised this classification after extensive diagnosis, including spline regression models.Results are available on request.
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These results suggest that large group differences in future wages emergenot only because white women are more likely to experience three or moretransitions during the crucial career-building stage, but also because smallershares of white compared with minority women make no job changes. Iffrequent job changing during the first four years after leaving school spurswage growth, minority women are at a clear disadvantage relative to theirwhite peers. Turnover rates decline five to eight years after school leaving, asworker-job matches are optimized, but white unskilled women exhibit aslight edge in their level of job mobility compared with their unskilledminority counterparts. Theoretically, prolonged turnover could underminewage growth and thus narrow the minority-white earnings gap, but whetherthis does in fact occur and whether wage penalties from turnover offset wagegains from early job mobility is an empirical question.
Among skilled women, white women are more likely than minority womento engage in job shopping during the first four years after leaving school, butalso are more likely than minorities to remain stably employed during thesecond postschool period. Presumably, job changes during this period are morecostly because skilled jobs usually require more firm-specific experience. Moregenerally, if the level and/or returns to job mobility change over time, there isreason to expect that the wage consequences of turnover will not be uniformamong demographic groups. The multivariate analysis tests this hypothesis.
Wage Growth
Because white, African-American, and Hispanic women have unequalstarting wages (see Figure 1), we use a value-added strategy to assess wagegrowth. Following Keith and McWilliams (1997) and Holmlund (1984), weestimate the (ln) wage at T8 while including T1 (ln) wage rate on the right-hand side, along with race and Hispanic origin. Appendix B reports regressionestimates for both unskilled and skilled women. The second model addsseveral covariates, such as whether women graduated from high school (un-skilled) or college (skilled), southern residence in T8, and birth cohort. To thisset of covariates, Model 3 adds several work-history variables of interest: thenumber of job-to-job transitions between T1 and T4 and between T5 andT8, and the percent of time spent in the labor force during each postschoolingperiod (T1–T4 and T5–T8). This specification reveals how both the timing ofpostschool work experience and the frequency of job turnover influence wagegrowth eight years after school departure. Model 3 also relaxes the assumptionof uniform returns to job mobility and experience for African-American,white, and Hispanic women by including interaction terms with job tran-sitions. Because minority women are less likely to be employed in any givenyear, it is unclear whether their lower average number of job transitionsreflects idleness or aversion to job changing. This issue is highly consequentialfor understanding how job mobility produces wage growth differentials.
Job Mobility and Early Career Wage Growth of Women 1205
Accordingly, Models 4 and 5 reestimate the disaggregated specification for twodifferent levels of labor force attachment (50 and 75 percent, respectively). Wefollow Light and Ureta’s (1990) criteria for identifying the cutoff for con-tinuously employed workers. Specifically, unskilled white women who worked75 percent of the time since leaving school represent the sample average. Usingthis threshold for comparisons across skill levels among similarly attachedworkers, 314 unskilled and 528 skilled women meet this criterion.
Before discussing how the timing and frequency of job mobility influencewage growth in postschooling years, two results from Appendix B are worthyof note. One is the black-white wage-growth gap of 13 and 11 percent forunskilled and skilled women, respectively (see base model). The second isthe added value of the job mobility Model 3 over Model 2. Inclusion of thejob-transition indicators significantly improves the explained variance of T8wages (incremental F statistically significant for both unskilled [11.4(14,619)] and skilled [6.2 (14,655)] women) and reduces the race wagedifferentials among unskilled and skilled women.
Using the point estimates reported in the Appendix, we facilitate inter-pretation of the results by calculating white women’s hourly wages eightyears after school leaving to illustrate differences between skilled and un-skilled women with different job mobility profiles (Table 3). Expanding thesimulation to African Americans and Hispanics considers the possibility ofdifferential returns to job changing among minority and nonminority wom-en with comparable levels of education and market attachment (Table 4).
Table 3 reports the predicted hourly wages (in log points) of white womenat T8 according to the timing and frequency of their turnover, holding allother variables at their mean. Results displayed in the top panel indicate thatunskilled white women who experience one or two job transitions duringtheir first four postschool years average $5.71 (1.74 log points) on an hourlybasis, which is significantly more than their immobile counterparts (1.60 logpoints or $4.95). The latter includes women who were continuously em-ployed and those who were less attached to market activity.
To assess the possibility that the gains from mobility depend on labor forceattachment, the subsequent columns present results for two levels of laborforce attachment, namely, women who worked more than half, or more thanthree-fourths, of the time in a given period. Restricting the sample to womenwho spent at least half of their postschool time in market activity yields similarresults, except that the average wage rates are higher, as predicted by humancapital theory. Eight years after leaving school, highly attached unskilledwomen (i.e., who worked more than three-fourths of the time) with zero, oneto two, or three or more transitions earned 1.72, 2.03, and 1.94 log points,respectively. This implies hourly rates of $5.57, $7.59, and $6.99, respectively.
White unskilled women who are highly attached to the market do notreap comparable wage benefits for high turnover during the latter part oftheir career-launching period. Specifically, highly attached white womenwho made three or more job transitions five to eight years after leaving
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TABLE 3
White Women’s Adjusted Hourly ln(wage) Eight Years Postschool by Skill, Timing, and Frequency of Job Transitionsa
(Standard Errors of the Estimate in Parentheses)
# Job-to-JobTransitions
Unskilled Women Skilled Women
T1–T4 T5–T8 All � $ LFA450% � $ LFA475% � $ All � $ LFA450% � $ LFA475% � $
aCalculated from estimates reported in Appendix B; all control variables are set to their respective sample means and to their average returns.bValues of job-to-job transitions for this period are set to the respective sample mean.cDifference is statistically significant in multivariate analysis—compared to zero job-to-job transitions.
JobM
obilityand
Early
Career
Wage
Grow
thof
Wom
en1207
TABLE 4
Adjusted Hourly Wages for Racial and Ethnic Job-Mobility Profiles Eight Years Postschoola
(Standard Errors of the Estimate in Parentheses)
Group Profile
GroupTransitionPatternb
GroupReturnsto JobMobility
Unskilled Women Skilled Women
All � $LFA
450% � $LFA
475% � $ All � $LFA
450% � $LFA
475% � $
White White White 1.67 $5.33 1.87 $6.48 1.95 $7.01 2.25 $9.53 2.33 $10.29 2.37 $10.70(0.03) (0.03) (0.03) (0.03) (0.03) (0.03)
aCalculated from estimates reported in Appendix B; all control variables are set to their respective sample means and to their average returns.bGroup transition pattern: mean job-to-job transitions of women in the respective sample.cProfiles 3 vs. 2 difference is significant at po0.05 level (patterns); based on T tests for the equality of the linear predictions.dProfiles 3 vs. 1 difference is significant at po0.05 level (returns); based on T tests for the equality of the linear predictions.
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school earned $5.59 (1.72 log points) per hour, while their statistical coun-terparts who remained with the same employer for the T5–T8 period earned$7.12 (1.96 log points) on an hourly basis at T8. Apparently, churningbehavior five or more years after leaving school is quite costly for unskilledwomen, even those who are highly attached to the market. On balance, theseresults indicate that both strong labor force attachment and early job shop-ping fuels unskilled women’s wage growth.
By comparison to unskilled white women, their college-educated racecounterparts portray a somewhat different picture of the association betweenjob mobility and compensation. Those who remain with one employer andaccumulate job-specific experience accrue significant wage gains, particularlyif they remain continuously employed. The predicted T8 hourly wage rateof highly attached, skilled white women who worked for one employerbetween T1 and T4 was $11.53 (2.45 log points), but women who madeone to two job changes averaged $10.94 (2.39 log points) on an hourlybasis. Moreover, their statistical counterparts who made three or more jobtransitions during their early work careers averaged only $10.12 (2.31) perhour. A similar pattern obtains for skilled white women who are less at-tached to the market, except that their average wage rates are lower. Duringthe latter phase of the postschool career-building period, skilled whitewomen incur more substantial penalties for frequent job transitions, whichare reflected in their lower wage rates.
The predicted wages reported in Table 3, while instructive about the as-sociation between job mobility and wage growth, do not address whether thereturns to job turnover are uniform among minority and nonminority women.Moreover, further analysis is needed to ascertain whether and what share of thewage gap stems from group differences in job-transition patterns. Three piecesof evidence from the foregoing justify decomposing the group differences inwage growth to job-mobility patterns and/or returns to job mobility: first, theadded value of the job mobility Model 3 over the baseline Model 2, as shownin Appendix B; second, the significant race gap depicted in the base model;and third, group differences in job-mobility patterns, as shown in Table 2.
To decompose group differences in wage growth to disparities in patternsand/or returns, we simulated three conditions of T8 hourly wages for Af-rican-American and Hispanic women: (1) white women’s average job-mo-bility pattern with minority women’s actual returns to job mobility; (2)minority women’s average job-mobility profile and white women’s returns;and (3) minority women’s actual average job-mobility profile and theiractual returns to turnover.6 These three simulations permit isolating the
6We assess the effect of group’s characteristics (namely, job transition patterns) and returnsusing all point estimates, regardless of their significance level, similar to standard decom-position techniques (Oaxaca, 1973; Duncan, 1968). To minimize risk of a Type II error, wecannot rule out the possibility that some parameters—which are very large in absolute valuebut not statistically different from zero—are related to T8 wages. This is because an im-precisely estimated large number is not exactly the same as precisely estimated zero.
Job Mobility and Early Career Wage Growth of Women 1209
mechanisms producing wage inequality, namely, those stemming fromgroup differences in the timing and frequency of job transitions versus groupdifferences in returns to job changing.
Table 4 presents results of the simulations as a set of predicted wages withall other variables and their coefficients set to their respective sample means.As in the prior tables, the calculations are reported separately for unskilledand skilled women. The top row presents white women’s predictedwages for the entire sample—assuming the average job-mobility pattern foreach category—and for two labor force attachment groups. Comparisonsbetween Row 3, which displays minority women’s predicted wage levels, andRows 1 and 2 reveal whether the wage consequences of job mobility forAfrican-American and Hispanic women stem from the pattern of job mo-bility (Row 3 vs. Row 1) or the wage returns to their job mobility (Row 3 vs.Row 2).
That the gap between Rows 1 and 3 is statistically significant for unskilledwomen confirms the tabular results regarding African-American women’slower level of job shopping, which is especially costly for the unskilled.Specifically, an unskilled African-American woman who worked 75 percentof the time after leaving school and experienced the average African-Amer-ican job-mobility pattern (Profile 3) earned $7.86 (2.06 log points) an hour.If she could replicate the job-mobility pattern of her white counterpart(Profile 1), her wages would rise to $8.46 (2.14 log points) by T8. However,if she received white women’s returns to her mobility pattern (Profile 2), heraverage hourly wages would be penalized by about 19 percent ($1.35). Thisindicates that the smaller wage growth witnessed by unskilled African-American female workers compared with comparable white workers derivesnot from low returns to job mobility, but rather from their relative im-mobility during the career-launching period—when job shopping fuels wagegrowth by optimizing the worker-job match.
Unskilled Hispanic women also could benefit financially by undertakingmore job changes during their early work career. The simulation exerciseindicates that unskilled Hispanic women’s wages would be 1 to 4 percenthigher (2.2 percent, on average) if they experienced the job-mobility patternof white women, other circumstances equal. With their actual job-mobilitypatterns and white women’s returns to job changes, unskilled Hispanicwomen’s wages would be higher still, on the order of 14 to 19 percent,depending on their level of market attachment during the period. Unlikeunskilled African-American women, highly attached Hispanic workers aredisadvantaged compared with their white counterparts both in terms of theirlevel of job mobility and their returns from early career turnover.
Results for college-educated women reveal some important differences vis-a-vis unskilled women. For skilled white women, making fewer job tran-sitions that permit accumulation of job-specific tenure appears to be anoptimal strategy for wage growth because it limits the substantial wagepenalties associated with turnover. However, skilled African-American
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women incur even higher wage penalties for job mobility than their whitestatistical counterparts. A typical, college-educated African-American wom-an who is highly attached to the market earns about $9.10 (2.21 log points)an hour, but with her white counterpart’s returns to job mobility, she wouldcommand $2 more on an hourly basis (reaching $11 an hour or 2.40 logpoints). The same holds for highly attached skilled Hispanic women, whowould average $10.86 (2.38 log points) per hour if returns to their job-turnover pattern were similar to those of white women compared with theiractual wage of $8.36 (2.12 log points). Because the tabular results showrelatively small differences in job-shopping patterns among skilled women,increased race and ethnic wage inequalities largely derive from unequalreturns to job mobility. A noteworthy caveat is that African Americansaverage fewer job changes than whites, especially during the early career, andthe simulation suggests that their relative stability produced significant wagegains. Conversely, the high variation in the levels of job mobility amonghighly attached Hispanic women did not produce similar benefits.
Discussion
We show that the employment dynamics of white, African-American, andHispanic women differ in ways that are likely to produce greater wageinequality over time. Compared with minority women, whites averagemore transitions during the four years following school departure and fewerjob transitions thereafter. This lifecycle pattern is conducive to optimizingthe results of job searches. Moreover, both the frequency and timing ofjob transitions differ along race and ethnic lines, as well as between skilledand unskilled women. For unskilled women, the wage benefits of jobmobility increase as labor force attachment rises. Continuously employedunskilled women reap the highest returns to job turnover during the firstfour postschool years; thereafter, the benefits of frequent job transitionsdiminish and excessive changes incur substantial wage penalties. However,we find no evidence that skilled white women’s job mobility boosts theirwage growth, and African-American women incur higher penalties thanwhites for job changing. The simulation exercise reveals that for unskilledwomen, racial and ethnic differences in wages stem largely from groupdifferences in the level of job mobility, whereas for skilled women, thesewage disparities largely stem from differences in the returns (penalties) to jobturnover.
Practically, our results imply that unskilled women facing a labor marketthat increasingly demands and rewards technical as well as cognitive skillscan improve their wage prospects through strategic job changing even be-yond the early career-building period. Because skilled women appear tosettle into good jobs relatively early in their work careers, the wage gainsfrom job mobility diminish early, giving way to job-specific tenure for
Job Mobility and Early Career Wage Growth of Women 1211
continued income growth. Differences in returns to mobility between skilledand unskilled women signal the importance of specialization in professionaljobs and longer on-the-job-training to achieve it.
The foregoing results underscore the importance of studying differencesin job shopping between minority and white women. Our results providelessons and directions for future research. First, to a large extent, minoritywomen’s lower levels of job mobility derive from their poorer educationalattainment and lesser attachment to the market. However, racial and ethnicdifferences in the pattern of job turnover still exist within education strataand/or among equally attached women. To consider whether minoritywomen’s lower level of job mobility results from a higher reservation wageand/or constrained local market conditions, we estimated a negative bino-mial model predicting the number of job-to-job transitions made by un-skilled and skilled women, respectively, during the first four years afterleaving school (results available on request). The results demonstrate thatconcentration in local labor markets that offer limited employment oppor-tunities (high unemployment) further constrain minority women’s jobmobility, especially for African Americans. Because other labor marketconditions, besides unemployment rate, might trigger women’s labor marketbehavior, further research is needed to identify other local labor marketconditions that limit career formation.
We also assess family circumstances that increase women’s economic un-certainty and thus their reservation wages, such as marital status, mother-hood, and having a partner with low market capacity. The results reveal thatfamily circumstances are more consequential in shaping the job-mobilityfrequency of skilled than unskilled women, especially Hispanics. Specifically,skilled Hispanic women who are married to a nonemployed spouse or whohave children engage in less job shopping. These household factors increaseminority women’s economic insecurity and curb their job mobility preciselywhen it is most likely to generate wage growth. Although it is conceivablethat employed minority women are risk aversive to new job prospects, fa-voring job security instead, other studies also show that minority womenalso face greater constraints in securing better jobs (Oettinger, 1996).
This analysis also addresses the potential endogeneity between wagegrowth and job mobility that may rise from unobserved heterogeneity. Wefind a major difference between unskilled and skilled women regardinginitial wages and the job-shopping process. The results show that women’sinitial wages do not influence job mobility among unskilled women. How-ever, consistent with findings from job-matching models, including studiesof men’s turnover (e.g., Topel and Ward, 1992), as well as for educatedwomen (Royalty, 1998), initial wages depress the level of turnover for high-skill women. These results support the notion that unobserved attributes,such as persistence, endurance, diligence, determination, and meticulous-ness, influence both the wage and job trajectories of skilled women. Thesefindings also shed light on the negative relationship between job mobility
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and future wages among skilled women. Combining these two pieces ofevidence demonstrates that both the wage and job trajectories of educatedwomen reward stability and penalize volatility. Skilled women optimize theirwage prospects by specializing, by acquiring job-specific skills, and by ac-cumulating job-specific tenure. This does not seem to be the case for the lessskilled for whom stability, at least during the early stages of career formation,is rewarded less than job shopping that improves the worker-job match.
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Appendix A: Definitions and Descriptive Statistics of Variables Included inthe Analysis (Means or Percents)
Variable Definintion Mean SD
Log wages at T8 Person-months hourly wagesdivided by the number ofnonmissing months with wageinformation
2.02 (0.598)
Log wages at T1 1.41 (0.504)# of job-to-job
transitionsJob-to-job transitions with the
maximum of 2nonemployment months inbetween T1–T8
2.95 (2.660)
% time spent in LF Number of employed monthsout of the total number ofmonths in each year multipliedby 100 T1–T8
76.87
Hispanic Hispanic 19.24African American African American 27.65White Nonblack, non-Hispanic 53.10HS Dropout If R completed less than 12 years
of education10.61
HS graduate If R completed 12 years ofeducation
38.03
Some college If R completed 13–15 years ofeducation
28.03
College graduate If R completed 161 years ofeducation
23.33
South, T1 If R lived in southern regions 40.07Year of birth
1961 28.331962 27.731963 28.261964 15.68
N 1,320
Job Mobility and Early Career Wage Growth of Women 1215
Appendix B: Estimates of T8 (Log) Hourly Wage Rates of Unskilled and Skilled Women (Robust Standard Errorsin Parentheses)
+Significant at 10%; nsignificant at 5%; nnsignificant at 1%.aControls: ln(wage T1).bControls: ln(wage T1), HS diploma/college diploma, south (T8), birth cohort.cControls: ln(wage T1), HS diploma/college diploma, south (T8), birth cohort, % time spent in LF T1–T4 and in T5–T8.
