IFR statistics show that Germany has consistently been a global top 5 robotics market for many years. They also provide distribution by industry. But what it does not show is who exactly is installing these robots and what distinguishes a robot user from a non-user. Data collected from nearly 16,000 plants by the Institute for Employment Research (IAB) of the Federal Employment Agency helps us to learn more about robot users in Germany.

Wie haben sich die Einkommen unterschiedlicher Bevölkerungsgruppen in Deutschland seit der Wiedervereinigung entwickelt? Unsere Studie untersucht die Entwicklung und Zusammensetzung des Nationaleinkommens entlang der Verteilung im Zeitraum von 1992 bis 2019. Während die untere Hälfte der Einkommensverteilung (unterhalb des Medianeinkommens) bis Mitte der 2000er Jahre reale Einkommensverluste verzeichnete, stiegen die Einkommen der oberen Mittelschicht (die obersten 10%, ohne das einkommensstärkste 1%) stetig. Die Spitzeneinkommen (oberstes 1%) blieben zwischen 1992 und 2019 relativ stabil. Arbeitseinkommen dominieren bei den unteren 99%, während das oberste 1% von Unternehmenseinkommen – insbesondere aus arbeitsintensiven Dienstleistungsunternehmen und freien Berufen – bestimmt ist. Unsere Ergebnisse sind zentral für die Debatte über Reformen der Sozialversicherungsbeiträge und der Einkommensbesteuerung.

In this study, establishment-level employment effects of investment grants in Germany are estimated. In addition to the quantitative effects, I provide empirical evidence of funding effects on different aspects of employment quality (earnings, qualifications, and job security) for the period 2004 to 2020. The database combines project-level treatment data, establishment-level information on firm characteristics and employee structure, and regional information at the district-level. For the estimations, I combine the difference-in-differences approach of Callaway and Sant’Anna (2021) with ties matching at the cohort level. The estimations yield positive effects on the number of employees, but point to contradicting effects of investment grants on different aspects of employment quality.

Why are children with lower socioeconomic status (SES) substantially less likely to be enrolled in child care? We study whether barriers in the application process work against lower-SES children — the group known to benefit strongest from child care enrollment. In an RCT in Germany with highly subsidized child care (N = 607), we offer treated families information and personal assistance for applications. We find substantial, equity-enhancing effects of the treatment, closing half of the large SES gap in child care enrollment. Increased enrollment for lower-SES families is likely driven by altered application knowledge and behavior. We discuss scalability of our intervention and derive policy implications for the design of universal child care programs.