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Nevertheless, we hope they will help shed light both on recent trends in the family gap in pay and possible factors that might help explain them. We are especially interested in the role of welfare reforms and changes in the labor market. In particular, we would like to know whether the timing of changes in the family gap for unmarried mothers coincide with welfare reforms, and how the family gap changes, both for women overall and for different groups, during different portions of the economic cycle.

Figure 1 shows the unadjusted mean wages of mothers and nonmothers over the sixteen periods in our study. Sample statistics, unweighted.

Gender pay gap: myth or reality?

For each of these percentiles, it appears that the gap is decreasing over time. However, over time, the trends also appear to diverge, mothers in the 10th and 25th percentile almost catching up to nonmothers at the end of the period, but with a small gap remaining. In contrast, comparison of median wages shows the gap disappearing by the end of the period.

Finally, for the 75th and 90th percentiles, mothers [End Page ] appear to overtake nonmothers over time, the positive wage differential being more distinct in the 90th percentile. Notes : Results from OLS regression of ln hourly wages in dollars on mother dummy variable. Sample is restricted to prime working age, twenty-five to forty-four years; Motherhood status is defined by the presence of children under age eighteen in the household. Please see figure A3 for a graph showing estimated coefficients on mother and confidence intervals and figures A4 for supplemental results comparing OLS with AIPW models.

Although they provide a glimpse of the trends in the family gap in pay, these descriptive results do not tell us how wages compare holding constant differences in characteristics between mothers and nonmothers for full descriptive statistics of these characteristics for mothers and nonmothers for each period, see tables A2 through A4.

Accordingly, figure 3 shows results from our regression models. The OLS results indicate a significant wage gap for mothers in each period that declines in magnitude over time, from 6. As a robustness check, we also provide AIPW estimates in figure A4 ; these models show a similar trend though with slightly smaller magnitudes and only a marginally significant less than 1 percent wage gap in the most recent period. We also examine trends in the motherhood wage differential by number and age of children in figures 4 and 5. Figure 4 shows that, over time, the family wage gaps for mothers whose youngest child is less than six years old and those whose youngest child is more than six years old, have diverged substantially.

Both groups were facing a 6 percent negative wage differential in and Over time, however, the gap decreased for the former group, who started facing a positive wage differential toward the end of the period under study. For the latter group, the wage gap increased over the s and s, and then decreased to 6 [End Page ] percent in to Figure 5 shows the wage differential by number of children. As expected, mothers with three or more children face the largest negative differentials in each period, though the gap itself appears to decrease over time.

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Trends for mothers with two children closely mirror the main model. Mothers with only one child, though, face a wage gap lower than the average for all mothers in each period, and no significant gaps in the most recent periods. In figure 6 , we successively add controls for part-time work, occupation, and industry.

In the most recent period, the wage gap is no longer significant. Controlling for occupation and for industry does not make much of a difference to the results. Main model figure 3 is included for comparison. Controls for part time, occupation, and industry are added successively.

Coefficient on mother for to in the model including control for part time only, is not significant. Graphs showing estimated coefficients on mother and confidence intervals available on request. We next examine the extent to which the family gap varies across groups and whether that variation has changed over time. We therefore repeat our main models OLS for subgroups defined by marital status, education, race-ethnicity, and immigration status figures 7 , 8 , 9 , and A5.

As shown in figure 6 , for married mothers, the family gap in pay declined and was replaced by a positive wage differential in the most recent period; for unmarried mothers, however, the negative wage differential persisted throughout the period with the exception of to when it was essentially zero , even rising to 10 percent over the to [End Page ] period.

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Coefficient on mother for — in the model including control for part time only is not significant. Examining the trends by race and ethnicity figure 8 , we again find considerable differences across subgroups. Comparing non-Hispanic white mothers with non-Hispanic black mothers presents some interesting trends. Until the beginning of the s, black mothers faced smaller percentage gaps than their white counterparts, but this pattern reverses between and as the family gap narrows for white mothers and increases for black mothers to reach 8 to 10 percent.

After this, the declining trend continues for white mothers such that between and , they face a marginally significant 1. For Hispanic mothers, the insignificant wage gap in the early years was followed by a significant 3 to 5 percent gap from to , but no significant gaps after that, except from to and from to , which each had a 4 percent gap.

These results are consistent with the expectation from prior studies that examine the [End Page ] family wage gap for shorter periods or at specific times and find that Hispanic mothers tend to face no wage gap or smaller differentials than other groups, and that black mothers tend to face smaller differentials than their white counterparts Waldfogel ; Budig and England ; Glauber ; but see Anderson, Binder, and Krause Turning to education subgroups in figure 9 , we find little evidence of a significant motherhood wage gap among those with less than a high school education throughout the period under study.

In contrast, we find significant gaps for the three more-educated groups but that these decline over the period. Women with the highest level of education college graduates tend to face the smallest gaps among the three more-educated groups: their wage gap fluctuates between 4 and 12 percent, falling to 2 percent from to and finally vanishing in the most recent period. For those with just a high school education and those with some college, we find a gradual decline in the wage gap over time from as much as 13 to 16 percent in the beginning of the period to 2 to 3 percent in the end.

Coefficients are also not significant for models showing the gap for non-Hispanic black mothers in the first two periods. All other coefficients are significant. Results by immigration status figure A5 show the absence of a family wage gap for foreign-born mothers through most of the period during which we can identify them from onward , and a 4 percent positive differential in the most recent data, among foreign-born mothers.

These results are consistent with the only other study that has looked at the [End Page ] family wage gap by immigration status Srivastava and Rodgers Coefficients are not significant in models for women with less than a high school diploma. Several explanations for a family wage gap at any given time are plausible. Drawing mainly on the work of Gary Becker , , researchers have emphasized three, which are not mutually exclusive.

First, mothers and nonmothers may differ in terms of their human capital. In addition to differences that may precede and be associated with the selection into motherhood, differences may arise subsequent to and as a result of motherhood. Second, mothers and nonmothers may work in different types of jobs, mothers being more likely to be concentrated in more family-friendly occupations or industries.

Individually and together, [End Page ] each of these ideas may explain the presence of a family wage gap except in the most recent periods for certain subgroups. These theories provide a useful framework for understanding the family gap in pay but may not fully explain how or why it changed during the period under study because of the role of several potentially contradictory socioeconomic and policy forces.

Most notably, mothers are returning to work sooner after childbirth than they did in the s and s. Among women with a first birth, only 10 percent were working three months after birth; slightly more than 10 percent were working twelve months after birth between and ; these proportions increased to 44 percent and 64 percent between and Laughlin Even though parenting has become more intensive, both mothers and fathers spending more time in childrearing than they did in earlier decades, the increase for fathers has been greater, almost tripling between the — and — periods Bianchi ; Parker and Wang These shifts might have helped close the wage gap between mothers and non-mothers by enabling mothers to conserve the effort that they would have earlier expended on nonmarket work.

These developments would be expected to lead to a decline in the family wage gap over the past forty years. Our results for married mothers are consistent with this expectation. On the other hand, changes in the composition of the workforce could negatively affect trends in the family gap.

In particular, the federal welfare reform following earlier federal and state reforms that began in the late s and early s pushed low-income single mothers into the labor market in large numbers. If those newly entering the labor market had lower human capital including unobserved factors that might lead to a larger wage differential for mothers than the women who worked before welfare reform, this change could have led to an increase in the family gap, particularly in the s.

We find some evidence of this in our results for black and Hispanic women who are more likely than non-Hispanic white women to be low income , and further evidence when we estimate our models separately for unmarried women who are most likely to be affected by welfare policy. Finally, policies to help mothers reconcile work and family have been fairly stagnant in the United States over the past several decades. Although the enactment of the Family and Medical Leave Act in was much heralded, the United States remains the only developed country without any national paid leave policy or universal childcare provision.

Cross-national research shows that motherhood wage gaps are likely to be relatively lower in countries with stronger work-family reconciliation policies Gornick and Meyers ; Misra, Budig, and Moller ; Budig, Misra, and Boeckman These results support the idea that childbirth requires reallocation of time, resources, and effort within the family.

It therefore follows that in the absence of strong labor-market attachment and employment protection policies, childbirth may become a potential point of temporary or permanent exit for women Becker , ; Blau and Kahn Given the importance of continued labor-force attachment and better job matches for wages, the lack of strong work-family policies is likely to have a negative effect on the wages of women with children.

These developments or lack thus predict an increasing, or at best, a stagnating family wage gap. We find these ideas helpful in explaining the divergent trends in the family wage gap by number of children. Although we cannot formally test explanations for what we find in terms of both change and lack of change in the family gap over time, we hope that our results will shed light on the role of these various factors. More immediately, they also provide some information about potential winners and losers as U.

The good news is that married women who have children seem to face much smaller gaps than they did in the past—indeed, their wages are now on a par or above those of married women without children.

But the bad news is that unmarried mothers seem to face larger family gaps than their married peers and larger gaps than their group faced in the past. Unlike in married families, we cannot look to their spouses to help take up the slack. We can however look to employer and public policies, including in the all important domains of paid leave, child-care, and workplace flexibility. Coefficients are not significant in models for foreign-born women except between and All other coefficients are significant.

Note : Sample is restricted to prime working age, twenty-five to forty-four years; motherhood status is defined by the presence of children under age eighteen in the household. Google Scholar. Victor Fuchs uses census data from and CPS data from and shows that women with children earn 7 to 9 percent less than childless women. Most recently, a cross-national study uses LIS data for the United States and recentered influence function regressions to find a striking 18 percent wage gap at the 10th percentile, none at the 90th, and 2 to 6 percent at different points in between Cooke See Gough and Noonan for a review of the U.

Many other studies examine the family gap in other countries and across countries see Todd ; Harkness and Waldfogel ; Sigle-Rushton and Waldfogel ; Gangl and Ziefle ; Cooke For a detailed review of the current U. For larger family wage gaps for married mothers, see Budig and England ; Glauber ; Loughran and Zissimopoulos Michelle Budig and Melissa Hodges include interactions of marital status with the number of children at different income quantiles and find that never-married women earned lower penalties than both the married and the divorced or separated in the bottom quantiles only, whereas ever-married women at the top earnings quantiles earned a motherhood bonus.

In earlier work, we find that the magnitude of the family gap has decreased over time for married mothers, but increased for never-married mothers Pal and Waldfogel Rebecca Glauber finds similar trend differences by marital status for the period from to In our prior work, we estimate the change in the family gap over to using data from the , , , and March CPS and adjust for selection using ordinary least squares and simple inverse probability of treatment weighted regressions.

We find that the wage gap in is not significantly different to that in , at about 5 to 6 percent. Glauber examines long-term trends by marital status for the period between and In our sample, we find 62 percent of the greater than two hundred hourly wage observations in the survey year, and 83 percent in the survey year, to include improbable hours or weeks of work reported, so they likely involve errors see also Schmitt ; Larrimore et al. Specifically, we take three decisions regarding variables to ensure as much consistency as possible. First, usual hours of work last year variable is only available from survey year.

So, for the to samples, we use the hours of work last week. This affects only 2. Three, weeks worked last year is available in intervals for the period before , so we use the midpoints of each interval. The way that cohabitors are identified is not completely consistent over the period. So in our main models we distinguish only between married and unmarried women.

The married category includes women who report being married, spouse present. The unmarried category includes all others married spouse absent, divorced, separated, widowed, and single. In supplemental models, we further divide unmarried women into those who are likely cohabiting and those who are not cohabiting. Race and ethnic origin are not consistently defined in the CPS over the period of our study. In our main models, we therefore only use the three race categories of white, black, and others, but in subgroup analyses, we also include Hispanic and separate the race categories into non-Hispanic white and non-Hispanic black.

We do not show the others category in subgroup analysis because the residual group changes too much between these two categorizations to be meaningful. When used individually to estimate a causal effect, both outcome regression and propensity score methods are unbiased only if the statistical model is correctly specified. AIPW and other doubly robust causal estimation techniques have been used in statistics, biostatistics and epidemiology but to our knowledge, have not previously been applied in the family gap literature.

Another challenge to causal estimation is selection into employment. Women, and particularly those with children, do not always participate in the labor market, and thus at any single point in time, the wage sample will contain a selected group of wage-earners. If that selection is correlated with wages for example, if the mothers who work are those who face the smallest wage penalties , estimates that do not take it into account will be biased. The standard method in the family gap literature to address such bias is the use of a selection correction model Heckman However, such models have important limitations.

They may not address all the factors associated with selection into employment and in particular those that are not observable. In addition, they rely on assumptions about the exogeneity of the predictors used in the selection regression most commonly other household income , and their results may be sensitive to which predictors are included. For this reason, we do not estimate such models. We do not include controls for part-time work, occupation, or industry in our subgroup analyses. For the last three periods, we are able to split the nonmarried mothers into two groups, cohabiting mothers and single mothers, and find that trends in the wage gap for nonmarried mothers are driven by single mothers, who face persistent negative wage penalties that reach a maximum of 10 to 11 percent from to Cohabiting mothers appear to face about a 7 percent wage gap in the earliest two periods, but no significant penalties thereafter, except from to Another possibly relevant change in the composition of the workforce is the increase in highly skilled women opting out of the labor market in the s.

However, according to Heather Boushey , this trend has been primarily driven by the weak economy and has affected both nonmothers and mothers, suggesting that it is not likely to explain changes in the wage gap between mothers and nonmothers see also Byker in this volume. Project MUSE promotes the creation and dissemination of essential humanities and social science resources through collaboration with libraries, publishers, and scholars worldwide.

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LOG IN. Ipshita Pal bio and Jane Waldfogel bio. Click for larger view View full resolution. Trends by Subgroup We next examine the extent to which the family gap varies across groups and whether that variation has changed over time. Direct correspondence to: Jane Waldfogel at j. Bonn: Institute for the Study of Labor. Anderson, Deborah J. Austin, Peter C. Avellar, Sarah, and Pamela J. Bang, Heejung, and James M. Baum, Charles L.

Becker, Gary S.