Understanding Employment Trajectories for Socioeconomically Disadvantaged Young Adults Can Support Their Well-being

Early adulthood is a critical life stage for education, employment, relationship formation, and reproductive health, but young adults’ experiences in these areas are highly varied. Using averages to describe youths’ experiences may miss meaningful differences that could alter their developmental trajectories. Understanding these trajectories—and their implications for youth of varying races, ethnicities, and genders—can help researchers, practitioners, and policymakers support young people’s development and ensure greater well-being into their adulthoods.

This brief summarizes some findings from a new report by Child Trends and the Brookings Institution that reveals different employment pathways taken by young adults from disadvantaged backgrounds through the use of trajectory analysis—a person-based approach that allows us to cluster people into meaningful patterns based on their employment earnings and the fringe benefits they receive. For our application of trajectory analysis, we started with a sample of youth who experienced socioeconomic disadvantage in adolescence, defined as those who met at least one of the following four criteria: lived in a low-income family, had no parent with a post-secondary degree, had a mother age 19 or younger at her first childbirth, or had a family that received public assistance. After identifying an initial sample, we followed these young adults from age 18 to 31 and clustered them into groups that follow a similar pattern. (For more information about our methods, see the Data and methods section at the end of this brief.)


Findings

We found four divergent employment pathways, or trajectories, that distinguish these young adults’ earnings and benefits patterns from age 18 to 31. Each trajectory represents a group of youth with strikingly different employment paths: In Group 1 (the lowest earnings group, representing 22% of the sample), young adults experienced essentially no growth in earnings or benefits from age 18 to 31; Group 2 (36% of the sample) experienced only slight increases by age 31 and Group 3 (34% percent) experienced moderate increases. Only Group 4 (9% of the sample) experienced substantial growth in earnings and benefits by age 31. Figure 1 shows the relative sizes of each group within our overall sample.


Figure 1: Percentage of Adults Who Experienced Adolescent Disadvantage Placed in Each Trajectory Group

Figure 1: Percentage of Adults Who Experienced Adolescent Disadvantage Placed in Each Trajectory Group

Figure 2, below, shows how each trajectory grouping fares over time on earnings and benefits. The benefits portion of the figure shows groups’ performance on the benefits index, which measures the average number of benefits received by youth in each group from age 18 to 31. The mean annual earnings portion of the figure shows the average yearly earnings in 2019 dollars for each trajectory group in the same age interval.


Figure 2: Earnings and Benefit Trajectories from Age 18 to 31 Among Young Adults from Disadvantaged Backgrounds

Figure 2: Earnings and Benefit Trajectories from Age 18 to 31 Among Young Adults from Disadvantaged Backgrounds

Note

Benefits are measured as an index scaled from 0 to 3, capturing whether a respondent’s employer offered health insurance, retirement benefits, or paid leave.

The four trajectories also illustrate racial and ethnic disparities in employment pathways that are reflective of persistent inequities within labor markets, the criminal justice system, and broader income disparities:

  • White people and men are overrepresented in the two highest-earning trajectory groups, while Black people and women are overrepresented in the lowest-earning group. White people make up more than half of the study population (58%); while they account for half of the adults in Groups 1 and 2, they make up 63 percent of Group 3 and 71 percent of Group 4.
  • Black people are overrepresented in Group 1 (31%) relative to their share of the study population (20%) and underrepresented in Group 3 (14%) and Group 4 (9%).
  • Latino or Hispanic people appear in most groups roughly proportionally to their share of the study population (17%), although they are somewhat underrepresented in Group 4 (14%).

We also used multivariate analysis to identify factors that predict membership in each trajectory group (including variables such as education, demographics, and job characteristics) and found that:

  • Youth with union membership and job training in their 20s are more likely to be in one of the highest-earning groups (Groups 3 and 4), while youth with higher education and military experience are more likely to be in the second-highest-earning group (Group 3).
  • Incarceration, work-limiting health conditions, or prolonged unemployment are strongly associated with lower-earning trajectories (Groups 1 and 2).
  • Being female and being Black greatly increases the probability of being in a trajectory group with low economic mobility, even after controlling for other factors.

Conclusion

This analysis of earnings growth during the early adulthood years highlights the presence of significant barriers to upward mobility for young people with socioeconomic disadvantages, as well as persistent systemic inequities for Black and Hispanic youth and young women. Research suggests that these inequities also compound: For example, women of color suffer from both gender and race discrimination, and experience significant wage gaps when compared to white men.

Research findings have long pointed to reforms that can offer young people better options. Due to systemic inequities within public education systems, reforming education to better help young people complete high school—and prepare them for postsecondary education—can help safeguard youth from severe economic deprivation. The nation’s criminal justice system also needs an overhaul to address the disproportionate incarceration of Black men; this analysis illustrates how incarceration doesn’t simply limit opportunities for upward mobility, but places obstacles in the way of youth that keep them trapped in poverty. Further, communities can provide youth who face socioeconomic disadvantages with new opportunities: Job training for youth in their early 20s may give them a strong push toward economic health and self-sufficiency.

Data and Methods

Data

We use the National Longitudinal Survey of Youth 1997 (NLSY97), a nationally representative survey of people born between 1980 and 1984 conducted by the Bureau of Labor Statistics. The NLSY97 is ongoing and has collected detailed information about participants’ education, training, employment, family formation, and other life experiences in 18 interview rounds, beginning in respondents’ teen years and continuing into their 30s. The richness of the NLSY97 allows us to identify a range of experiences associated with socioeconomic disadvantage that goes beyond family income. In addition, we draw on data in these 18 survey rounds to capture a variety of circumstances that we anticipate will impact economic mobility.

Trajectory analysis

We use a statistical approach called group-based trajectory modeling, or trajectory analysis, to identify different employment pathways. Averages are informative but never tell the whole story, and neither do measures collected at just one or two points in time. Trajectory analysis is a person-based approach that allows us to identify meaningful differences among a group of people over time that otherwise may be missed.

Our trajectory analysis segments the study population into distinct groups based on their similarities on two factors: their annual earnings and employer-provided benefits from ages 18 to 31. This approach identifies different earnings and benefits patterns, or trajectories, experienced over the entire period, and associates individuals with the trajectory that most closely matches their actual experience. The trajectory group assignment encompasses both earnings and benefits, so each person belongs to one group only (for instance, a person cannot belong to Group 1 for earnings and Group 2 for benefits).

Multivariate analysis

Once we identified trajectory groups, we estimated multinomial logistic risk models to identify factors that may explain individuals’ membership in each group, including measures of background characteristics such as education, marital status, gender, race/ethnicity, parental wealth, and cognitive test scores.

Please see the technical appendix from the Brookings Institution for more details about our data and methods.

Suggested citation

Piña, G., Moore, K. A., & Warren, J. (2022). Understanding employment trajectories for socioeconomically disadvantaged young adults can support their well-being. Child Trends. https://doi.org/10.56417/9027u5978f