Abstract
This study investigates the effects of adults’ enrollment in and graduation from a two-year college on their hourly wages and occupational status in U.S. by employing a growth curve model and a piecewise model. College enrollment reduced hourly wages and occupational status by 13.8 % and 2.74 points, respectively. Less-educated workers whose wages were the main source of income were more likely to compromise their occupational status for a better work-study balance and thus to realize wage penalties during schooling. While a two-year college degree acquired in adulthood had significant positive effects on hourly wages and occupational status, the said positive economic returns from the degree were moderated by their self-esteem.
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Notes
Psychologist conceptualized this situation as ego threat (Leary et al. 2007).
Sample weight was applied to individuals in the level-2 model to adjust for the unequal sample selection probability of an oversample for Blacks and Hispanics.
In 1990, every participant in NLSY79 was aged over 25, the age at which literature often distinguishes adult learners from traditional college students.
These metrics allowed for identification of the typical patterns suggested by Mincer’s human capital earning function (Mincer 1974). Furthermore, these metrics were designed to find a way to identify growth in the Socioeconomic Index specified.
Refer to the equations in the next page.
Variances in the linear and quadratic terms for work experience were significant but variances for local unemployment rates and three schooling-related time-points were not significant.
Multiparameter tests allowed for simultaneous investigation of the statistical significance of each level-2 predictor on each level-2 equation, without inflating the statistical significance level (Raudenbush and Bryk 2002).
Analyses were conducted using xtmixed command of Stata.
The results of GMM models are displayed in Appendix 1.
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Appendix 1
Appendix 1
A comparison of group membership derived from GMM and piecewise regression model
This study demonstrated that adult learners’ wage rates depend on college enrollment and completion. However, adult learners who enrolled in community colleges may consist of unobserved subgroups. Thus we investigate additionally how known group distinction according to college enrollment, a priori, is related to latent group membership. First, employing the GMM, we identified the distinctive shape of the subgroup’s wage trajectories (Duncan et al. 2002; Vaughn and Witko 2013). Then, we applied a multinomial logistic regression to predict the subgroup membership by a priori, college enrollment status.
GMM identifies several trajectories of homogeneous individuals through classification based on similar patterns of growth trajectories (Nagin 1999). Comparing model fit indices such as Bayesian Information Criteria (BIC) and Entropy we determined the number of latent classes (Skrondal and Rabe-Hesketh 2004). The smallest BIC provides the number of latent trajectory classes fitting the data better. An Entropy value closer to one is preferred. BIC and Entropy displayed in Table 6 indicate the three class solution. Figure 4 displays the fitted growth trajectories for the three latent classes; 42.2 % of individuals (Class 1) were classified into the inverse U-shape-pattern class, 26.1 % of individuals (Class 2) were classified into the linear-shape-pattern class, and 26.7 % of individuals (Class 3) were classified into the U-shape-pattern class. Individuals in Class 2 and 3 compared to those in Class 1 undergo wage drops by some time point and experience wage gains after that point.
Fitted growth lines using growth mixture model. The number 0 in work experience stands for 6 years after high school graduation
We tested whether class membership for three types of wage trajectories depends on the college enrollment status. Table 7 shows the results of a multinomial logistic regression examining the relationship between latent class membership and college enrollment status. Class 1 was used as a reference. For college enrollment status, the odds of being in Class 2 are 0.766 times the odds for being in Class 1. The odds of being in Class 3 were 0.846 times that of being in Class 1. These results indicate that individuals in Class 2 and 3, the class that adult learners likely belong to, will undergo wage drops during schooling compared to those in Class 1, whereas those in Class 2 and 3 were more likely to experience wage gains after degree than those in Class 1. These were similar to the results of piecewise regression modeling during and after college degree, which are displayed in Table 5.
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Kim, KN., Baker, R.M. The Assumed Benefits and Hidden Costs of Adult Learners’ College Enrollment. Res High Educ 56, 510–533 (2015). https://doi.org/10.1007/s11162-014-9351-x
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DOI: https://doi.org/10.1007/s11162-014-9351-x