There is a relatively consistent negative relationship between adolescent depressive symptoms and educational achievement (e.g., grade-point average [GPA]). However, we are less certain of the causal direction for this association due to the lack of longitudinal data with both indicators measured across at least two time periods, and due to the lack of application of more sophisticated contemporary statistical techniques. We present multivariate results from a large longitudinal cohort-sequential study of high school students (N = 7,317) with measures of self-reported depressive symptoms and self-reported GPAs across multiple time points (following McArdle, 2009; McArdle et al., 2001) using an ethnically diverse sample from Hawai‘i. Contemporary statistical techniques included: bivariate dynamic structural equation modeling (DSEM); multi-group gender-and-ethnic DSEMs; ordinal scale measurement of key outcomes; and imputation for incomplete longitudinal data. The findings suggest that depressive symptoms affect subsequent academic achievement, and not the other way around, especially for Native Hawaiians as compared to non-Hawaiian females. We further discuss the scientific, applied, and methodological-statistical implications of the results, including the need for further theorizing and research on mediating variables. We also discuss the need for increased prevention, early intervention, screening, identification, and treatment of depressive symptoms and disorders. Finally, we argue for utilization of more contemporary methodological-statistical techniques, especially when violating parametric-test assumptions.