The major finding of this study is that the rise in female labor force participation rates from 1956 to 1975 did not lower the overall level of experience. The widening gap between male and female earnings is attributed to the effects of discrimination and role differentiation. (SK)

Uses data from the National Longitudinal Survey of the High School Class of 1972 to study how male students' employment while in college influences their academic performance, persistence, and actions after college. (Author/CH)

Previous studies of the relationship between body weight and wages have found mixed results. This paper uses a larger data set and several regression strategies in an attempt to generate more consistent estimates of the effect of weight on wages. Differences across gender, race, and ethnicity are explored. This paper finds that weight lowers wages…

Labor market attachment differs significantly across young black, Mexican, and white men. Although it has long been agreed that potential experience is a poor proxy for actual experience for women, many view it as an acceptable approximation for men. Using the NLSY, this paper documents the substantial difference between potential and actual…

A comparison of the earnings and work experience of associate, diploma, and baccalaureate registered nurses (RNs) found that diplomas are the least attractive route to licensing. Although associate degrees are superior to bachelors', the many baccalaureate graduates may be attracted by better access to nonstaff positions, nonmonetary rewards, and…

A matched sample of Social Security and Current Population Survey records is used to determine life-cycle earnings patterns of White males. Estimated effects of schooling and experience compare well with other studies, but interaction effects with cohort do not. Military experience plays a powerful role in earnings differences across cohorts.…

Compares the earnings of technicians who have an Associate degree to the earnings of technicians who have other educational backgrounds. Discusses several other variables: training and experience; and the impact of sex, race, socioeconomic background, location of residence, and type of employer. (CT)