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.

The world price of oil is determined by the interactions of multiple producers and consumers who face different constraints and shocks. We show how this feature of the oil market can be used to estimate local and global elasticities of supply and demand and provide a rich set of testable restrictions. We develop a novel approach to estimation based on full-information maximum likelihood that generalizes the insights from granular instrumental variables. We conclude that the supply responses of Saudi Arabia and adjustments of inventories have historically played a key role in stabilizing the price of oil. We illustrate how our structural model can be used to analyze how individual producers and consumers would dynamically adapt to a geopolitical event such as a major disruption in the supply of oil from Russia.

The standard economic model of occupational choice following a basic Roy model emphasizes individual selection and comparative advantage, but the sources of comparative advantage are not well understood. We employ a unique combination of Dutch survey and registry data that links math and language skills across generations and permits analysis of the intergenerational transmission of comparative skill advantages. Exploiting within-family between-subject variation in skills, we show that comparative advantages in math of parents are significantly linked to those of their children. A causal interpretation follows from a novel IV estimation that isolates variation in parent skill advantages due to their teacher and classroom peer quality. Finally, we show the strong influence of family skill transmission on children’s choices of STEM fields.

It is well established that female students perform better when taught by female professors. However, little is known about the mechanisms explaining these gender match effects. Using administrative records from a German public university, which cover all programs and courses between 2006 and 2018, we show that gender match effects are sizable in smaller classes, but are absent in larger classes. These results suggest that direct and frequent interactions between students and professors are crucial for gender match effects to emerge. In contrast, the mere fact that one’s professor is female is not sufficient to increase performance of female students.