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 analyse the impact of robot adoption on employment composition using novel micro data on robot use in German manufacturing plants linked with social security records and data on job tasks. Our task-based model predicts more favourable employment effects for the least routine-task intensive occupations and for young workers, with the latter being better at adapting to change. An event-study analysis of robot adoption confirms both predictions. We do not find adverse employment effects for any occupational or age group, but churning among low-skilled workers rises sharply. We conclude that the displacement effect of robots is occupation biased but age neutral, whereas the reinstatement effect is age biased and benefits young workers most.

Does increasing common ownership influence firms’ automation strategies? We develop and empirically test a theory indicating that institutional investors’ common ownership drives firms that employ workers in the same local labor markets to boost automation-related innovation. First, we present a model integrating task-based production and common ownership, demonstrating that greater ownership overlap drives firms to internalize the impact of their automation decisions on the wage bills of local labor market competitors, leading to more automation and reduced employment. Second, we empirically validate the model’s predictions. Based on patent texts, the geographic distribution of firms’ labor forces at the establishment level, and exogenous increases in common ownership due to institutional investor mergers, we analyze the effects of rising common ownership on automation innovation within and across labor markets. Our findings reveal that firms experiencing a positive shock to common ownership with labor market rivals exhibit increased automation and decreased employment growth. Conversely, similar ownership shocks do not affect automation innovation if firms do not share local labor markets.

Die deutsche Wirtschaft ist noch immer im Abschwung. Seit nunmehr zwei Jahren folgen abwechselnd minimale Zu- und Abnahmen von einem Quartal auf das nächste. Zuletzt nahm das Bruttoinlandsprodukt (BIP) im zweiten Quartal 2024 um 0,1% ab. Zuvor war es zwar um 0,2% gestiegen (vgl. Abbildung 1), aber auch dies reicht nicht aus, um die negative Produktionslücke zu verringern. Die Produktion in der Industrie und vor allem am Bau ist im zweiten Quartal spürbar gesunken. Auch im laufenden dritten Quartal ist die Stimmung der Unternehmen schlecht. Neben einer schwachen Nachfrage für Exportgüter gibt es eine Reihe von Gründen, warum ein Aufschwung noch nicht in Gang kommt: So wirken neben hohen Zinsen und Energiepreisen auch eine richtungslose Politik sowie eine Vielzahl geopolitischer Krisenherde investitionshemmend. Auch der nach wie vor hohe Krankenstand belastet die Wirtschaft. Alles in allem dürfte das Bruttoinlandsprodukt (BIP) laut IWH-Flash-Indikator im dritten Quartal 2024 um lediglich 0,2% steigen, was erneut keine konjunkturelle Trendwende bedeutet. Eine kräftigere Belebung könnte sich aufgrund steigender Realeinkommen am Jahresende einstellen.

Using a newly collected dataset at the plant level from 2014 to 2018, we provide the first microscopic portrait of robotization in Germany and study the correlates of robot adoption. Our descriptive analysis uncovers five stylized facts: (1) Robot use is relatively rare. (2) The distribution of robots is highly skewed. (3) New robot adopters contribute substantially to the recent robotization. (4) Robot users are exceptional. (5) Heterogeneity in robot types matters. Our regression results further suggest plant size, high-skilled labor share, exporter status, and labor shortage to be strongly associated with the future probability of robot adoption.

Establishment closures have lasting negative consequences for the workers displaced from their jobs. We study how these consequences vary with the amount of skill mismatch that workers experience after job displacement. Developing new measures of occupational skill redundancy and skill shortage, we analyze the work histories of individuals in Germany between 1975 and 2010. We estimate difference-in-differences models, using a sample of displaced workers who are matched to statistically similar non-displaced workers. We find that displacements increase the probability of occupation change eleven-fold. Moreover, the magnitude of post-displacement earnings losses strongly depends on the type of skill mismatch that workers experience in such job switches. Whereas skill shortages are associated with relatively quick returns to the earnings trajectories that displaced workers would have experienced absent displacement, skill redundancy sets displaced workers on paths with permanently lower earnings. We show that these differences can be attributed to differences in mismatch after displacement, and not to intrinsic differences between workers making different post-displacement career choices.