The Roy-Borjas model predicts that international migrants are less educated than nonmigrants because the returns to education are generally higher in developing (migrant-sending) than in developed (migrant-receiving) countries. However, empirical evidence often shows the opposite. Using the case of Mexico-U.S. migration, we show that this inconsistency between predictions and empirical evidence can be resolved when the human capital of migrants is assessed using a two-dimensional measure of occupational skills rather than by educational attainment. Thus, focusing on a single skill dimension when investigating migrant selection can lead to misleading conclusions about the underlying economic incentives and behavioral models of migration.

We study a mentoring program that aims to improve the labor-market prospects of school-attending adolescents from disadvantaged families by offering them a university-student mentor. Our RCT investigates program effectiveness on three outcome dimensions that are highly predictive of later labor-market success: math grades, patience/social skills, and labor-market orientation. For low-SES adolescents, the mentoring increases a combined index of the outcomes by over half a standard deviation after one year, with significant increases in each dimension. Part of the treatment effect is mediated by establishing mentors as attachment figures who provide guidance for the future. Effects on grades and labor-market orientation, but not on patience/social skills, persist three years after program start. By that time, the mentoring also improves early realizations of school-to-work transitions for low-SES adolescents. The mentoring is not effective for higher-SES adolescents. The results show that substituting lacking family support by other adults can help disadvantaged children at adolescent age.

This paper uses a new empirical design to explore how labor market polarization affects individuals’ incentive to pursue education funded on the margin by student debt. We argue that the labor market polarization–where automation replaces mid-skill and mid-education-level job–changes the marginal benefits of education and training and sharpens incentives to incur student debt. We advance a new measure of labor market polarizations that allows to capture the heterogeneity of this phenomena across geographies and time. Using this measure, we find that U.S. CBSAs that experience deeper labor market polarization see an increase in student debt balances and in the number of people pursuing student debt. On average, the decline in middle-skill jobs and wages has little effect on individuals’ ability to pay down existing student debt. The effects are most pronounced in ZIP codes with lower average credit scores, lower incomes, and higher share of the minority population.