Pathways to High School Graduation: Dynamic Modeling-Based Microsimulation of School Enrollment and Youth Employment

Lingxin Hao, Johns Hopkins University
Guihua Xie, Johns Hopkins University

This paper proposes a new approach to examining the pathways through school enrollment and youth employment to high school graduation, with a substantive focus on the effects of state welfare policies. Our approach represents an advancement in the demography of schooling. Based on dynamic models of multiple discrete states, multi-state life tables, and microsimulation, our approach makes several extensions. First, it produces microdata-based prediction rather than aggregate-based prediction. Second, it provides the size of the effect of key explanatory variables on the population patterns, net of other covariates, with inferential statistics such as confidence intervals. Third, it predicts the differential timing effects of key explanatory variables. Drawing on three waves of the most recent longitudinal data on adolescents, the National Longitudinal Survey of Youth (NLSY97), the study models and simulates the pathways to high school graduation from age 14 to age 19. It also simulates these pathways using CPS 1994-2000 data.