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Monthly Labor Review Online

April  2003, Vol. 126, No.4

Précis

ArrowJobs, gender, and marriage
ArrowMarriage, motherhood, and earning power
ArrowMidwest work force composition

Précis from past issues


Jobs, gender, and marriage

There are at least three theories of gender segregation of occupation extant, and, like faculty departments, they often do not communicate much with each other. Feminist scholars, according to M. V. Lee Badgett and Nancy Folbre, often suggest it is a straightforward matter of continuing discrimination by employers. Sociologists look to socialization and social norming. Economists say occupational sorting might be a rational maximization of the work and family problem.

Badgett and Folbre suggest that as none of these is actually inconsistent with the others, it might be best to cross disciplinary boundaries. In their article, a maximization model is extended to include the marriage market and the marriage market accounts both for positive assortative mating (meaning likes often attract) and for a social norm under which gender nonconformity in occupation reduces one's desirability as a marriage partner.

Although their model and hypothesis were thus "economistic," their data gathering used a factorial survey method that has been used by both economists and sociologists. Here, the survey was designed as a set of "vignettes" in the form of personal ads. Several such "ads" were shown to a panel that was asked how many positive responses each ad would receive. Badgett and Folbre "…. believe that respondents’ subjective evaluations of the attractiveness of the biographies to other people correspond closely to the respondents’ own valuations of the characteristics in each personal ad."

Their statistical analysis used dummy variables for occupations of high and low status and masculine or feminine employment patterns (for example, day care worker and family therapist as low and high status "feminine" occupations and auto mechanic and orthopedic surgeon as low and high status "masculine" occupations). Badgett and Folbre conclude that "…wherever the gender associated with an occupation matters within a status category, gender nonconformity is penalized." In particular, men in high-status but feminine jobs are rated less highly than men in high-status masculine occupations and conversely, women in low- status masculine jobs are rated less highly than women in low-status feminine jobs. The model, conclude the authors, suggests that women face a lower rate of return in the marriage market to investments in human capital than do men and that gender conformity is rewarded for both sexes.

Source: Badgett, M.V. Lee, and Nancy Folbre, "Job Gendering: Occupational Choice and the Marriage Market," Industrial Relations, April 2003

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Marriage, motherhood, and earning power

Does marriage itself correlate with wages? In the case of men, economists have documented a substantial wage premium for being married, a premium that carries over even to divorced men. Does a similar premium exist for women?

Abbigail L. Chiodo and Michael T. Owyang say no. Once other factors such as education, experience, and children are taken into account, they find, "[T]he effect of marriage on women’s wages becomes statistically insignificant." They do find evidence, however, of a correlation between the timing of marriage and women’s earnings. Women who delay marriage have, on average, higher wages than women who marry early. Economists speculate that such an effect suggests that the early years of a career are crucial to developing the human capital needed to raise one’s wage profile.

Another difference between the wage analyses for women and men is the effect of children. Although there is little impact of children on the marriage premium for husbands, women’s average earnings go down if children are present. As was the case for marriage, delaying childbearing has a positive effect on wages, if only to attenuate the losses associated with having a family. In one study cited by Chiodo and Owyang, early childbearing was associated with roughly a 4-percent decline in wages and later childbearing was associated with barely a 1-percent loss.

Chiodo and Owyang conclude, "Therefore, the theories that explain the relationship between men’s wages and their marital status are necessarily different from the theories that explain this relationship for women. In short, this is because, compared to the average married man, the average married woman faces much more dramatic tradeoffs between her career and her family responsibilities."

Source: Chiodo, Abbigail J., and Michael T. Owyang, "Marriage, Motherhood and Money: How Do Women's Life Decisions Influence Their Wages?" Federal Reserve Bank of St. Louis, The Regional Economist, April 2003

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Midwest work force composition

The impact of labor composition by education and experience on productivity in the Midwest is almost exactly the same as the impact of labor composition on productivity figure for the Nation. In both cases, according to a Worker Quality Index calculated by Daniel Aaronson and Daniel Sullivan of the Federal Reserve Bank of Chicago, there has been an increase in worker "quality" (measured by education and experience) that has accounted for about 10 percent of productivity growth since the mid-1960s.

The way the Midwest has arrived at the average is interesting, however, and gives Aaronson and Sullivan some concern. The Midwest has both fewer high school dropouts than other regions, a fact that increases the quality of the region’s labor composition, and fewer college graduates, a fact that works in the opposite direction. The authors point out in the Chicago Fed Letter that with the rate of high school graduation so high in the Midwest, the region will have to increase its share of workers with post-secondary training to continue to advance.

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We are interested in your feedback on this column. Please let us know what you have found most interesting and what essential reading we may have missed. Write to: Executive Editor, Monthly Labor Review, Bureau of Labor Statistics, Washington, DC. 20212, or e-mail MLR@bls.gov



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