We measure selection among high-skilled emigrants from Germany using predicted earnings. Migrants to less equal countries are positively selected relative to nonmigrants, while migrants to more equal countries are negatively selected, consistent with the prediction in Borjas (1987). Positive selection to less equal countries reflects university quality and grades, and negative selection to more equal countries reflects university subject and gender. Migrants to the United States are highly positively selected and concentrated in STEM fields. Our results highlight the relevance of the Borjas model for high-skilled individuals when credit constraints and ⇤ Matthias Parey: University of Essex and Institute for Fiscal Studies, m.parey@es-sex.ac.uk, Jens Ruhose: Leibniz Universität Hannover, ruhose@wipol.uni-hannover.de,

A key element of economic development policies has been the improvement of the human capital of workers through such policies as upgrading public schooling or enticing the migration of skilled workers. Most empirical research has, however, focused more narrowly on school attainment, both distorting the empirical assessments and removing much of the analysis from the actual policy debates. We have two objectives in this study. First, we develop new measures of worker skills, or knowledge capital, that are designed to incorporate both quantity and quality of skill investments. Second, we investigate the extent to which difference in knowledge capital can explain variations in income across US states. The more complete measurement of worker skills proves very important in understanding state growth and development.Not much attention has been paid to the substantial income differences among US states and the role of differences in state human capital as a possible source.

After the collapse of the Soviet Union, more than 3 million people with German ancestors immigrated to Germany under a special law granting immediate citizenship. Exploiting the exogenous allocation of ethnic German immigrants by German authorities across regions upon arrival, we find that immigration significantly increases crime. The crime impact of immigration depends strongly on local labor market conditions, with strong impacts in regions with high unemployment. Similarly, we find substantially stronger effects in regions with high preexisting crime levels or large shares of foreigners. JEL-Code: F22, J15, K42, R10

We propose a regression-adjusted matched difference-indifferences framework to estimate pecuniary and non-pecuniary returns to adult education. This approach combines kernel matching with entropy balancing to account for selection bias and sorting on gains. Using data from the German SOEP, we evaluate the effect of work-related training, which represents the largest portion of adult education in OECD countries, on individual social capital and earnings. As the related literature, we estimate positive monetary returns to work-related training. In addition, training participation increases participation in civic, political, and cultural activities while not crowding out social participation. Results are robust against a variety of potentially confounding explanations. These findings imply positive externalities from work-related training over and above the well-documented labor market effects.

We study whether early tracking of students based on ability increases migrant-native achievement gaps. To eliminate confounding impacts of unobserved country traits, we employ a differences-in-differences strategy that exploits international variation in the age of tracking as well as student achievement before and after potential tracking. Based on pooled data from 12 large-scale international student assessments, we show that cross-sectional estimates are likely to be downward-biased. Our differences-in-differences estimates suggest that early tracking does not significantly affect overall migrant-native achievement gaps, but we find evidence for a detrimental impact for less integrated migrants. JEL-Code: I21, J15, I28