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This study begins by examining the impact of both cognitive and noncognitive skills on between- and within-education group wage inequality, using data from the National Longitudinal Survey of Youth 1979 (NLSY79) and quantile regressions. While the economic return to education has been proposed as a parsimonious explanation for rising wage inequality and its currently high level, this account focuses mainly on between-education group wage inequality and the demand for cognitive skills. Results from my analysis shows that (1) while the economic return to education is the robust explanation for wage inequality, both cognitive and noncognitive skills contribute significantly to reducing the college wage premium and wage dispersions within college graduates; (2) noncogntive skills play a more pronounced role in wage inequality among college graduates; and (3) the wage effect of both skills as an early predictor of earnings strengthens as workers reach their prime ages in the labor market. These findings suggest that the family may be an important institutional actor responsible for wage inequality.

In the subsequent chapter, I use data from the National Longitudinal Study of Adolescent Health (Add Health) and the NLSY79 to investigate the role of cognitive and noncognitive skills in individual patterns of educational assortative mating in adolescence and adulthood. This paper argues that to the extent that skill differences are associated with education-based mate selection, intergenerational mobility operates at an intimate level of the mate selection process. Multinomial logistic regression results show that cognitive and noncognitive skills are positively associated with the probability of transitioning into marrying college graduates and, to a lesser degree, with that of dating college-bound partners. I also find a gender difference in the role of skill differences: noncognitive skills play a more salient role in education-based mate sorting for women, whereas it is cognitive skills that primarily do so for men, indicating a normative attitude toward mate selection that regards "smartness" as more attractive to women than to men. These findings imply that the intergenerational transmission of familial resources affects children's mate selection by not simply investing in their educational attainment but also strengthening their cognitive and noncognitive skills.

Finally, I reevaluate the socioeconomic effect of teenage childbearing. Despite a 30-year debate about the consequences of adolescent fertility, finding its "true" effect still has been elusive. This concern stems from (1) theoretical considerations of early motherhood as a harmful event and/or its higher likelihood among disadvantaged young women and (2) methodological challenges against selection bias. Alternative models have been developed, but tend to rely on strong assumptions and unrepresentative samples. This paper extends the extant literature by taking a counterfactual approach using propensity score matching, conducting a sensitivity analysis employing the Rosenbaum bounds to address selection bias on unobserved covariates, and using data from Add Health. Results show that while teen mothers' preexisting socioeconomic disadvantages and their lower level of cognitive and noncognitive skills play a nontrivial role, teen motherhood has significantly negative effects on early socioeconomic outcomes with the exception of public assistance receipt. The sensitivity analysis suggests that selection bias due to unobserved covariates would have to be very powerful to nullify these findings.

Methods: Longitudinal and cross-sectional data were obtained from four nationally representative surveys: National Health and Nutrition Examination Survey, National Longitudinal Study of Adolescent Health, National Health Interview Survey, and National Longitudinal Surveys of Youth (NLSY79 and NLSY97). The analysis tracked age trends in BMI by time, which allowed for the examination of how BMI changed during the transition to adulthood and whether the patterns of change varied by period. Data best suited for trend analysis were identified. Age trends in BMI by gender and race were graphed and regression analysis was used to test for significant differences in the trends using the National Health and Nutrition Examination Survey and National Longitudinal Study of Adolescent Health.

Results: BMI increased sharply in the adolescent ages, beginning in the 1990s and among young adults around 2000. This age pattern of BMI increase was more dramatic among females and blacks, particularly black females.

Conclusions: BMI increased during the transition to adulthood and these increases have grown larger over time. Obesity prevention efforts should focus on this high-risk transition period, particularly among minority populations.