INEQUALITY AND MOTHERHOOD Paula England New York University Department of Sociology pengland@nyu.edu

A note about sources: All tables or graphs in this presentation are calculations of my coauthors and I, using the NLSY79 data (all waves) I will not list authors for past literature, or show complete results But if you email me at pengland@nyu.edu I will send you the forthcoming paper including all this

How the Motherhood Penalty Varies by Skill and Wage Paula England New York University (Coauthors: J. Bearak, M. Budig, M. Hodges) Paper is forthcoming in American Sociological Review

Past Literature After adjustments for selectivity, motherhood depresses the wages of U.S. women. Suggested explanations are that mothers spend years out of employment, losing experience work part-time, which pays less well per hour shift to more mother-friendly jobs that pay less have lowered productivity, even net of experience are victims of employers’ discrimination against mothers Persistence of effects in analyses with FE suggests causal effects

A Puzzle About Who “Pays” Higher Proportionate Penalties Wilde, Batchelder, & Ellwood, 2010 (NBER): Women with higher cognitive skill pay higher penalty. Budig and Hodges, 2010 (ASR): Women with lower wages pay a higher penalty. Both use NLSY79 with fixed effects. Budig and Hodges use quantile regression; Wilde et al. split sample by skill.

Terminology Total effect: effect of motherhood on wages, after controlling for things probably exogenous to motherhood (e.g. education) but not controlling for experience. Includes the indirect effect of motherhoodexperiencewage, and the net effect below. Net effect: effect of motherhood on wages net of the exogenous factors above and net of experience. This tells you if motherhood affects wage among those with the same experience, probably because employers discriminate against mothers (relative to other women) and/or motherhood adversely affects productivity.

Why Would (Total or Net-of-Experience) Penalties Differ by Skill or Wage? Lower skill/wagehigher total penalty if they have lower level of experience Higher skill/wagehigher total penalty if they have higher returns to experience Higher skill/wagehigher net penalty if performance in high skilled jobs is key to the bottom line and motherhoodperformance (real, perceived) Lower skill/wagehigher net penalty if workers can’t bargain for flexibility, and can’t afford things needed to keep motherhood from affecting their (real or perceived) performance

Data and Methods Use white women’s sample from NLSY, a national probability US sample, 14-21 years old in 1979 Pool panel data, 1979-2010; observations are person-years when women not students and had a wage Dependent variable: Ln hourly wage in constant 1996 $ Independent variable: # of children Main models are unconditional quantile regression with person fixed effects, with and without controls for experience Fixed Effects remove omitted variable bias from unmeasured, unchanging characteristics of the person

Exploring how Combinations of Skill and Wage Level Affect the Penalty Use quantile to see if penalties more or less at higher wage levels Interact all variables with Skill to see if penalties more or less at higher skill levels

Quantile Regression: CQR and UQR QR provides separate coefficients at any desired percentile (quantile) of the dependent variable CQR used by Budig and Hodges. Uses all observations to compute coefficient at each quantile, but weights them differently, e.g. For 20th, weight up observations below 20th so they total 80% of cases, and weight down those above 20th so they total 20% of cases Killewald and Bearak (2014, ASR) point out that CQR the wrong model to assess whether women with absolutely low wages have high penalties; it tells us whether penalties are higher for those whose wages are high relative to covariates (e.g. education) UQR (Firpo et al. 2009, Econometrica) uses a different procedure such that quantiles are defined by the unconditioned distribution of the dependent variable. Coefficients, however, still adjust for covariates.

Control Variables in UQR Regressions Predicting Ln Wage Equation 1: Geography, Age, Education, Age X Education Equation 2: Above plus Marital Status, Spouse’s Earnings (0 if single) Equation 3: Above plus person fixed effects Equation 4: Above plus hours of experience and tenure, and whether current job is part-time, and interactions of all these with education I’ll focus on Equations 3 (total penalties) and 4 (penalties net of experience, tenure, current PT status)

White Women’s Total Penalty Per Child, by Wage Quantile and Skill   Quantile .20 Quantile .80 Difference, .2&.8 High Skill -.04* -.10* * (Difference) Bottom 2/3 Skill -.07* -.05* From Eq 3 in Table 1 with Fixed Effects, no control for experience, tenure, or part-time

White Women’s Net Penalty Per Child, by Wage Quantile and Skill   Quantile .20 Quantile .80 Difference, .2&.8 High Skill -.02* -.04* ns (Difference) * Bottom 2/3 Skill -.03* -.00 From Eq 4 in Table 1 with Fixed Effects, with controls for experience, tenure, or part-time

Discussion re Net-of-experience Penalties These net penalties are much smaller than total penalties (e.g.~ half or less, depending on skill/wage level) Penalties somewhat higher for highly skilled, high wage women but differences not always significant Thus we make no strong claims about discrimination or performance effects differing by skill or wage

Discussion re Total Penalties Total penalties highest for highly skilled, high wage women They are mostly in management and professions, and lose little experience (see Tab 2) which should reduce their penalties But they have higher rates of return to experience, so what little experience they forego is very costly Results so far for whites; blacks have lower penalties, though these don’t come from lower returns to experience

Conclusion Women advantaged on skill, wage, race have higher proportionate total motherhood penalty Evidence suggests that the differences in penalties by skill and wage are because having higher returns to experience makes even the small amount of time these women take out for motherhood expensive

Let’s discuss

Extra slides for Q&A

Total Penalty: Equation 3 (No Control for Experience) Quantile   .2 .3 .4. .5 .6 .7 .8 .8 - .2 Diagonal Top skill 1/3 -.04 -.06 -.07 -.08 -.10 * / * Difference n.s. Bottom skill 2/3 -.05 \ n.s. Penalty Net of Experience, Tenure, Part-time: Equation 4 -.02 -.01 /n.s. -.03 -.00 \*