Lawyers’ Salaries: Mommy Penalties, Daddy Bonuses, and Pure Gender Effects
Even among highly educated professionals, there is a persistent difference in the salaries of men and women. Untangling the reasons for that difference is quite difficult, and it involves as a threshold matter trying to figure out whether there are factors other than gender that explain why women earn less than men. Some studies have suggested that the difference in salaries is not in the first instance about the gender of the worker but about the worker’s status as a parent or non-parent. Some empirical research, for example, has found that men with children earn more than everyone else in their fields but that there are no detectable differences among women with children, women without children, and men without children.
I recently finished a draft of a paper (available here) in which I looked at the results of two surveys of graduates of the University of Michigan Law School from the classes of 1970 through 1996. These surveys were developed by Richard Lempert, David Chambers, and Terry Adams, who used the data from the first survey to study the effects of race on lawyers’ careers in their fascinating article: “Michigan’s Minority Graduates in Practice: The River Runs Through Law School,” 25 L. & Soc. Inquiry 395 (2000). Professor Lempert and his co-authors administered a follow-up survey that gathered information about gender and parental status; and they allowed me to use their data for the empirical analysis summarized in my draft paper.
Most of my paper is focused on technical matters of survey techniques and econometric analysis. For those who find such matters tedious or worse, the most direct discussion of the statistical results is in the introduction and conclusion and on pp. 30-32. My tentative results confirm the “daddy bonus” that others’ have found in other studies, with the range of estimates suggesting a 15-20% salary advantage for fathers. Unlike previous studies, however, I also find a strong suggestion that women …
with children endure a “mommy penalty,” earning perhaps 10-15% less than the childless (and thus 25-35% less than fathers). I also find some weaker statistical support for the hypothesis that childless women earn less than childless men, with my estimates suggesting an 8-9% difference disfavoring women.
The wonderful thing about empirical research is that every interesting set of results demands further study. Can my results regarding the salary losses for mothers and childless women be confirmed by further research? Although I also look at differences such as part-time status, the ages of children, and whether the children are living with the lawyer-parent, what other evidence should be taken into account in future studies?
Perhaps a more intriguing question is why the salary disadvantages against women and in favor of men largely show up through parental status. (Parenting itself still tends to be characterized by massive differences in gender roles, of course. Even if all of the difference in salaries between men and women were mostly about differences in child-rearing, therefore, this would simply relocate the question of how sexism continues to affect women and men differently.) Because this draft is mostly a technical discussion of empirical results, I speculate only briefly on the reasons for the daddy bonus, offering three possibilities: fathers feel the need to work harder to bring home more bread for the family, men wait to become fathers until their salaries are high enough to support a growing family, and (my cynical favorite) fathers shirk childcare responsibilities by hiding in the office and incidentally raising their salaries.
Fortunately, the surveys from which I drew my data are now being superseded by an even larger study of Michigan law graduates, with more detailed questions and more respondents from more graduating classes. This will allow researchers to use “panel data” techniques and other sophisticated methods of searching for statistical relationships.
Because I plan to be one of those researchers, I would be especially interested in readers’ suggestions (either on the Comment board or via email: email@example.com) regarding both how to improve and refine the regressions and how to explain the results. The best way to analyze empirical issues is to analyze data from as many angles as possible, so I will be very appreciative of any constructive suggestions.