New Skills, New Jobs: Return Migration, Skill Transfers, and Business Formation in Mexico

Numerous studies have documented a high propensity for self-employment and business formation among return migrants relative to non-migrants. The literature points to the importance of remitted savings, migration duration, and number and types of jobs abroad for business formation upon return. Implicit in this scholarship is the assumption that migrants acquire not only financial capital, but also human capital, which expands their opportunities upon return. Empirical work has demonstrated how the transfer of formal human capital, such as language skills and professional credentials, influences the mobility pathways of professional return migrants. More recent research has also found that the transfer of informal human capital, such as social and technical skills learned on the job, shape the mobility pathways of return migrants with little schooling. Absent from this scholarship, however, are studies that directly test the relationship between the transfer of informal human capital and the odds of business formation among return migrants. In this paper, we address this gap. Using a multidimensional skills variable, which includes social, technical, and English language competences, we measure and test the relationship between skill acquisition and transfer and business formation among return migrants. Drawing on findings from a survey of 200 return migrants and 200 non-migrants in Mexico, we show that return migrants who successfully acquire and transfer new skills across the migratory circuit often leverage their new knowledge to launch businesses. Our findings have wide implications for how social scientists conceptualize and measure human capital formation across the migratory circuit

Escuelas de la calle y autobuses escuela: provisión de educación informal en Francia

A la luz del acceso cada vez más limitado a la escolarización por parte de los solicitantes de asilo e inmigrantes en Francia, han surgido iniciativas de voluntarios para brindar una educación informal indispensable

Alternative causal inference methods in population health research: Evaluating tradeoffs and triangulating evidence.

Population health researchers from different fields often address similar substantive questions but rely on different study designs, reflecting their home disciplines. This is especially true in studies involving causal inference, for which semantic and substantive differences inhibit interdisciplinary dialogue and collaboration. In this paper, we group nonrandomized study designs into two categories: those that use confounder-control (such as regression adjustment or propensity score matching) and those that rely on an instrument (such as instrumental variables, regression discontinuity, or differences-in-differences approaches). Using the Shadish, Cook, and Campbell framework for evaluating threats to validity, we contrast the assumptions, strengths, and limitations of these two approaches and illustrate differences with examples from the literature on education and health. Across disciplines, all methods to test a hypothesized causal relationship involve unverifiable assumptions, and rarely is there clear justification for exclusive reliance on one method. Each method entails trade-offs between statistical power, internal validity, measurement quality, and generalizability. The choice between confounder-control and instrument-based methods should be guided by these tradeoffs and consideration of the most important limitations of previous work in the area. Our goals are to foster common understanding of the methods available for causal inference in population health research and the tradeoffs between them; to encourage researchers to objectively evaluate what can be learned from methods outside one's home discipline; and to facilitate the selection of methods that best answer the investigator's scientific questions