Youth Transitions: Life Events and Labor Market Behavior

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This article focuses on the population of young adults in Wyoming tracked over time by linking a range of relevant databases together around the concept of key choices that labor market entrants must make in the context of persistent social norms and changing economic events. This article is part of a larger observation of young people’s interaction with the labor market by R&P, including the decreasing numbers of youth obtaining a driver’s license (Moore, 2014) and the out-migration of youth from Wyoming (Glover, 2012).

Enhancing consumer choice in the field of training and education, and meeting employer need for skilled workers are overall goals of a U.S. Department of Labor Workforce Data Quality Initiative (WDQI) grant received by the Research & Planning (R&P) section of the Wyoming Department of Workforce Services. These WDQI grants focus on the research component of a larger employment and training effort to bring outcomes to the labor market desired by workers and employers. Research focuses on understanding choices and programmatic efforts leading to jobs consistent with long-term economic security by studying labor market interactions for selected populations and the workforce as a whole.

The research strategy used for this article can be defined as program impact evaluation. In order to successfully conduct employment program evaluation research, labor market trends in comparison to the behavior of individuals need to be independently distinguishable over time. This paper examines the transitions of a selected age segment in the population in terms of life events (e.g. marriage, household formation, child bearing, career choice, and out-migration) associated with labor market behavior over time. As mentioned previously, economic conditions interacting with life events affect market outcomes for individuals.

Longitudinal analysis of diverse, linked datasets represents a new tool to address traditional research questions as well as emergent questions developed in response to an evolving economy. Consequently, an objective of this paper is basic methodological research intended to inform subsequent applied research. Observations from this paper strongly suggest that in order to understand how young adults interact with the economy, the most productive analysis will result in shifting the focus from individuals to households as the unit of analysis.

Research has shown that the aging population in the United States may be affecting patterns of deferred marriage and household formation (Leppel, 1991), but little has been written on the life events coinciding with or following the initial departure of a young person from their parent’s home. Ermisch & DeSalvo (1997) examined the relationship between economic conditions and the timing of initial departure from one’s parent’s house as the primary residence, and found that the primary destination following the departure was living with a partner. In addition, the authors found that women tend to leave the home nearly two years earlier than men. Given the likelihood that a young person leaves home and forms a new household with a mate (as opposed to living alone or living with friends), R&P analyzed at what age life events like marriage and birth of a first child occur in order to better understand how these events may affect labor market outcomes.

To explore how conditions and life events affect outcomes, R&P analyzed demographics and vital statistics from 2002 to 2014 in Wyoming’s labor market. Further, Unemployment Insurance (UI) wage records were used longitudinally to track labor market participation and behavior within Wyoming and its partner states1 between 2002 and 2012. In order to do this, R&P selected three cohorts (groups): individuals who were age 18 in 2002, 2005, and 2009. Each cohort was tracked independently in this analysis, but interaction can take place between cohorts (e.g., marriage) and individuals may enter the state and interact with another individual who was not part of the original cohorts. The overall goal of this analysis was to empirically define a set of age categories (e.g., 18 to 22) that are relevant in terms of choices individuals make and that strike a balance between an abundance of detail and aggregations that are relevant.

Methodology and Results

First Marriage and Birth of First Child

R&P currently has access to vital statistics records from the Wyoming Department of Health. These records include births, marriages, divorces, and deaths. Among the life events likely to affect working behavior among young adults is household formation. For this reason, this analysis focuses on age of marriage and age of first birth. Age was calculated at the time of event (birth or marriage). To capture the period of birth and marriage relevant to the cohorts, the date of marriage or birth must have occurred between 2002 and 2012 by single year of age for individuals ages 18 to 30.

Table 1
Figure 1

Figure 1 and Table 1 represents a composite of first marriages that includes all three previously mentioned cohorts. Table 1 shows that females marry at younger ages compared to males up until the age of 23. Beginning at age 24, more males marry for the first time than females, with the difference between the genders being smaller. For example, the number of females who marry at the age of 18 during the time period examined was 1,506 (5.4%) compared to 529 (2.2%) males. This result indicates that males enter marriage at a later age than females.

Table 2
Figure 2

Another key turning point in an individual’s life is the birth of a first child. Figure 2 and Table 2 show the number and percent of individuals (parents) by age at birth of their first child. Table 2 shows that females are younger than males at the birth of the first child. Approximately one in four females (25.5%) during this period were between the ages of 18 and 20 at the birth of their first child. At age 25, the number of individuals having a first child is roughly equal for both genders (N Females = 2,401, Males = 2,398). Among all males ages 18 to 30 during this time, 10.0% (2,452) were age 27 at the birth of their first child.

Based upon these descriptive, cross-sectional results, it may be appropriate to group genders differently in terms of marriage and births, since males and females experience these events at different points in their lives. Subsequent analyses should be cognizant of the different ages at which males and females marry and have children. It is important to note that Wyoming has a relatively small population, and decisions about migration and household formation are related to age and economic opportunity (Gallagher, 2015, p. 21).

Retention Rate and Instability Index

Figure 3

Job stability is an important part of earnings growth, and one response to job instability may be out-migration. This section discusses the age at which individuals change labor markets, and the concept of job instability. This analysis examines retention for the three previously mentioned cohorts (18-year-olds from 2002, 2005, and 2009). These three periods were selected to represent different labor market conditions: the 2002 Cohort represents a period of modest growth, the 2005 Cohort represents the beginning of a rapid expansion, and the 2009 Cohort represents the beginning of a rapid decline (see Figure 3). R&P currently has complete wage record data through 2014. Wage records from 2002 to 2012 were used in this analysis to identify individuals who were 18 years of age and had wages in Wyoming in the three years previously mentioned – the starting point for each cohort – and tracked them over the course of four to 10 years.

Retention in Wyoming and employment instability by gender and cohort over the 10-year period from 2002 to 2012 are discussed in this section. Our interpretation of the data at this point is that instability is a precursor to outmigration.

Figure 4
Table 3

Retention rates for females and males from the three cohort years are shown in Table 3. A total of 3,751 males were identified as 18 years of age in the 2002 Cohort. Of this original cohort, 83.1% remained working in Wyoming at the age of 19 (2003). However, by the time they reached age 28, just over half (53.2%) remained working in Wyoming (see Figure 4). The retention rates for the 2005 and 2009 cohorts followed similar trajectories.

In the 2002 Cohort, 3,613 females were 18 and working in Wyoming. As shown in Figure 4, 84.1% of females remained working in Wyoming at the age of 19 in 2003; this was similar to the proportion of males from the 2002 Cohort who were still working in Wyoming at age 19 (83.1%). By the time they were 28, fewer than half of those females (46.2%) were still working in Wyoming. Retention rates for females from the 2005 and 2009 cohorts followed similar trajectories.

Further, the retention rate for males from the 2002 Cohort appears to level off beginning at age 25, whereas females from this cohort continued to leave Wyoming’s labor market at a consistent rate. A visual inspection of Figure 4 suggests little difference in the retention rates for males and females from the three cohorts. This may be a subject for future research.

Figure 5

As suggested earlier, instability – and the implied associated lack of earnings or access to obvious career options, exacerbated by household formation income needs – may contribute to out-migration. Because understanding successful outcomes in the labor market requires the ability to measure continuity, sustainability, and labor market coherence, R&P developed the instability index. The instability index is calculated using the method outlined by Glover (2000), which is illustrated in Figure 5.

Table 4
Figure 6

The instability index uses measures of job turnover and continuous employment (i.e., employment in the prior quarter, reference quarter, and subsequent quarter with the same employer). The instability index is shown for the three cohorts in Figure 6 and Table 4. As with retention, instability is associated with age, regardless of gender. Both retention and instability decline almost in direct relationship to age. According to Glover, there are four possible categories an individual can fall into: entry (E), exit (X), both entry and Exit (B), and continuous (C). Continuous employment is considered a stable situation where an individual remains with the same employer for three consecutive quarters. The other three categories are considered unstable employment. The instability index is calculated by dividing the sum of the three unstable categories by the sum of all four categories (E+X+B / E+X+B+C). The index is meant to act as an indicator of labor market activity at an individual level.

As seen in Figure 6, the overall the trend in instability decreases as both males and females age. Clearly, based on these limited observations, the key factor in instability is age and not gender. The instability index can also decrease based on the numbers of hires and exits relative to continuous employment. For example, for youth ages 18 to 20 working in Wyoming from 2009 to 2014, the majority of hires were in the retail trade and leisure & hospitality industries (Hammer & Holmes, 2015). Hires in the retail trade and leisure & hospitality industry tend to be short-term and seasonal, as opposed to industries like public administration and health care, where hires do not follow a seasonal pattern. This concept is illustrated by Gallagher (2015, p. 18). In contrast to factors such as age and industry of hire, periods of economic growth seem to have little impact on the instability index.

Relatively stable growth and relatively rapid growth have little impact on instability. In contrast to older individuals, employment opportunities for young people tend to be represented by a hire, followed shortly by an exit. On the other hand, when the economy experiences a downturn, stability increases due to the fewer number of hires. For both genders, the 2009 Cohort was more stable than the 2002 and 2005 cohorts. For males age 20, instability declined from 62.5% (2005 Cohort) to 58.3% (2009 Cohort; see Table 4).

For males, employment instability is relatively higher at a younger age, while the instability for females is higher at an older age. For females from the 2002 Cohort, instability leveled off from age 25 through 28. This result may be due to individuals finishing some form of education (e.g., college, technical school) that allows them to find more stable employment. Further, as seen in Figure 2, a majority of females are having their first child before the age of 25, and family obligations may interact with the ability (and desire) to find stable employment during the first few years of their children’s lives. These trends are not pronounced but are candidates for further investigation.

Employment in Partner States

Table 5

Table 5 shows the number and percentage from each cohort found working in Wyoming or a partner state as a primary state of earnings. A youth’s primary state of earnings is defined as the state in which he or she earned the highest wages in a given year. Table 5 also shows the number and percentage of individuals from each cohort who were not found working in Wyoming or a partner state during a given year. There appears to be a correlation between age and when a person exits Wyoming’s labor market, as nearly one-third of each cohort left Wyoming’s labor market between the ages of 19 and 21. After age 21, the exits from Wyoming’s labor market continued at a much slower pace.

Of the 7,373 18-year-olds in the 2002 Cohort, there were 6,932 (94.0%) whose primary state of earnings was Wyoming. By 2012, Wyoming was the primary state of earnings for 3,533 (47.9%) of those individuals from the 2002 Cohort. As individuals from the 2002 Cohort aged, a greater number earned their primary wages in a partner state. In 2002, 441 (6.0%) of these 18-year-olds had primary wages in a partner state. By 2012, 1,454 (19.7%) individuals from the 2002 Cohort had wages in a partner state. The remaining 2,386 (32.4%) could not be found working in Wyoming or a partner state.

Figure 7

The percentage of individuals from each cohort with Wyoming as their primary state of earnings is shown in Figure 7. As this figure illustrates, a smaller proportion of individuals from the 2002 Cohort had primary wages in Wyoming than the other two cohorts after age 19.

Figure 8

Figure 8 shows the percentage of individuals working primarily in a partner state by cohort. A smaller percentage of 18-year-olds from the 2009 Cohort (3.9%) had primary wages in a partner state compared to the 2002 (6.0%) and 2005 (5.3%) cohorts. According to Hammer & Holmes (2015), during the economic downturn in Wyoming, a smaller percentage of people ages 18 to 20 found work compared to the rest of the population. The lower starting point of the 2009 Cohort may be due in part to fewer opportunities for younger workers who entered the market during a decline.

Figure 9

As the individuals in each cohort aged, a larger number were no longer found working in Wyoming or a partner state (see Figure 9). For example, of the 7,373 individuals in the 2002 Cohort, 2,386 (32.4%) could not be found working in Wyoming or a partner state in 2012. As noted by Glover (2012), this category includes individuals who moved to a state with which R&P does not have a data sharing agreement, those who exited the labor force for other reasons, and those who are deceased. This category also includes self-employed individuals, and employees of railroads, the federal government, and the armed forces.

Age and different economic conditions may have affected how each cohort behaved in the labor market. For example, as shown in Figure 8, the percentage of individuals from the 2002 Cohort working primarily in partner states grew at a steady pace through age 24. However, the percentage of individuals primarily working in a partner state from the 2005 Cohort slowed after age 21. Both of these events occurred in 2008, the final year of economic expansion in Wyoming. A smaller percentage of individuals from the 2009 Cohort worked primarily in a partner state than either of the other cohorts. These younger individuals entered the labor market during Wyoming’s recent economic downturn, which may have affected their decision to leave Wyoming for employment in a partner state. Individuals from the 2002 Cohort had been in the labor market for several years before the downturn, and thus had more work experience, possibly increasing their ability to find and retain employment in other labor markets.


The goal of this article was to investigate the life events and labor market activity of those ages 18 to 30 to determine how age segments might be grouped for purposes of analysis for both theoretical relevance and efficiency in presentation. Developing age groups allows researchers to conduct sound program evaluation research by reducing bias based on normal life events. Using UI wage records and vital statistics administrative databases, R&P found that males and females differ in terms of age at first marriage and birth of first child. Females tend to marry and have their first child before the age of 22, while males tend to be older before reaching these events. This finding suggests that age at first marriage and birth should be controlled when conducting program evaluation research by gender. Either of these life events could significantly impact employment opportunities and work search intensity.

This article also demonstrated that between the ages of 18 and 22, retention in a specific labor market decreases regardless of gender or economic conditions (see Figures 4 and 5). For males, retention tends to stabilize around the age of 25, while this effect was not observed for females. Labor market instability was found to decrease over time for both genders. When economic conditions are poor (the recent downturn in 2009), younger individuals have a lower level of instability compared to their more experienced counterparts. This effect may be due to a person’s perception of the lack of job opportunities and experience which would enable them to change jobs.

Finally, younger individuals are more likely than older individuals to move out of Wyoming to a partner state. However, individuals who are between the ages of 18 and 21 during times of an economic downturn are less likely to move to other states for employment. Job opportunities in other states may be viewed as scarce, and moving to another labor market involves a risk.

In terms of specific age groups that should be assessed when conducting program evaluation research, several key factors should be noted. Due to the differences in genders regarding age at first marriage and first birth, controlling for this variable statistically will be the most appropriate method of reducing bias. Propensity score matching techniques should be completed separately for males and females with a covariate specific for both events. Based on the retention rates, labor market instability, and interstate mobility, several age groups could be defined. Individuals between the ages of 18 and 20 experience higher instability and are retained at the same employer less than those between the ages of 21 and 24. Those over the age of 25 begin to experience labor market stability and retention with the same employer remains consistent.

Finally, it is evident that the unit of analysis should be modified from the individual to the household. At the beginning of each cohort, this analysis implicitly focuses on individuals as the unit of economic analysis. At some point in the age of each cohort, the unit of analysis changes from the individual to the household. The shift from individual to household units represents an important proportion of each cohort. Decisions regarding career choice, necessary income levels, birth of children, and migration are then made at the household rather than the individual level. For this reason, future strategies regarding the analysis of youth transition must take this transformation into account.


Ermisch, J., and DiSalvo, P. The economic determinants of young people’s household formation. Economica, 64(1997).

Gallagher, T. (2015). Chapter 2: Student interaction with the labor market. Workforce Data Quality Initiative Report No. 1 for Wyoming School Attendance and Employment, 2006 to 2013. Retrieved May 7, 2015, from http://doe.state.wy.us/LMI/education_we_connect/WDQI_Pub1.pdf

Glover, T. (2000). The instability index as a measure of labor market activity. Wyoming Labor Force Trends, 37(3). Retrieved December 12, 2014, from http://doe.state.wy.us/lmi/0300/toc.htm

Glover, T (2012). A Decade Later: Tracking Wyoming’s Youth into the Labor Force. Retrieved May 7, 2015, from http://doe.state.wy.us/LMI/w_r_research/A_Decade_Later.pdf

Hammer, L. & Holmes, M. (2015). Fewer youth working in Wyoming. Wyoming Labor Force Trends, 52(3). Retrieved May 7, 2015, from http://doe.state.wy.us/LMI/trends/0315/a1.htm

Leppel, K. (1991). Demographic effects on household formation patterns. Journal of Real Estate Research, 6(2). Retrieved May 8, 2015, from http://econpapers.repec.org/article/jreissued/v_3a6_3an_3a2_3a1991_3ap_3a191-206.htm

Moore, M. (2014). The decline in teen drivers: What it may mean for Wyoming. Wyoming Labor Force Trends, 51(9). Retrieved May 7, 2015, from http://doe.state.wy.us/LMI/trends/0914/a1.htm

1R&P currently has data sharing agreements with 11 states: Alaska, Colorado, Idaho, Montana, Nebraska, New Mexico, Ohio, Oklahoma, South Dakota, Texas, and Utah.


Table of Contents

May 2015, Vol. 52
No. 5

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