In this article, we consider how individuals’ long-term employment trajectories relate to wage inequality and the gender wage gap in the United States. Using more than 30 years of data from the National Longitudinal Survey of Youth 1979 sample, we identify six employment trajectories for individuals from ages 22 to 50. We find that women across racial/ethnic groups and Black men are more likely than White and Hispanic men to have nonsteady employment trajectories and lower levels of employment throughout their lives, and individuals who have experienced poverty also have heightened risks of intermittent employment. We then assess how trajectories are associated with wages later in careers, at ages 45–50. We find significant variation in wages across work trajectories, with steady high employment leading to the highest wages. This wage variation is primarily explained by work characteristics rather than family characteristics. Finally, we examine gender variation in within-trajectory wages. We find that the gender wage gap is largest in the steady high employment trajectory and is reduced among trajectories with longer durations of nonemployment. Thus, although women are relatively more concentrated in nonsteady trajectories than are men, men who do follow nonsteady wage trajectories incur smaller wage premiums than men in steady high employment pathways, on average. These findings demonstrate that long-term employment paths are important predictors of economic and gender wage inequality.
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“Opt out” is in quotation marks because scholarship suggests that leaving work for family is not always voluntary (Stone 2007).
We apply NLSY custom weights, which adjust for attrition in the longitudinal sample (see https://www.nlsinfo.org/weights/nlsy79).
Some studies on long-term employment have used a measure of hours worked rather than employment (e.g., Damaske and Frech 2016). We deviate from this measure to study labor force attachment variation rather than intensity of employment. Although both measures lend unique benefits, the measure that we use allows us to focus on variation in employment versus nonemployment rather than on levels of work.
NLSY uses “Black/Non-Hispanic,” “Hispanic,” and “Non-Black, Non-Hispanic.” We sometimes refer to this last group as “White,” but we recognize that it could include additional racial/ethnic groups as well. See https://www.nlsinfo.org/content/cohorts/nlsy79/topical-guide/household/race-ethnicity-immigration-data.
These are weighted averages.
Hours worked per week are top-coded at 100 per week (5,200 per year), with 7,000+ coded as missing. Our results are robust to these wage and hours coding decisions; models are available upon request.
Results are robust if the dependent variable measures the wages at the oldest working age from ages 45 to 50.
See section 3 of the online appendix for information on missing data.
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We are grateful to Michael Rosenfeld, Koji Chavez, Ariela Schachter, Ted Mouw, and Demography reviewers and editors for comments on earlier versions of the manuscript. The NLSY79 survey is sponsored and directed by the U.S. Bureau of Labor Statistics and conducted by the Center for Human Resource Research at The Ohio State University. Interviews are conducted by the National Opinion Research Center at the University of Chicago. Both authors contributed equally to this work.
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Weisshaar, K., Cabello-Hutt, T. Labor Force Participation Over the Life Course: The Long-Term Effects of Employment Trajectories on Wages and the Gendered Payoff to Employment. Demography 57, 33–60 (2020). https://doi.org/10.1007/s13524-019-00845-8
- Life course
- Labor force