Research

Abstract
We analyze the impact of robot adoption on employment composition using novel micro data on robot use of German manufacturing plants linked with social security records and data on job tasks. Our task-based model predicts more favorable employment effects for the least routine-task intensive occupations and for young workers, the latter being better at adapting to change. An event-study analysis for robot adoption confirms both predictions. We do not find decreasing employment 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.

Abstract
We analyze the impact of robot adoption on female employment. Our analysis is based on novel micro data on robot use by German manufacturing establishments linked with social security records. An event study analysis for robot adoption shows increased churning among female workers. Whereas hiring rises significantly at robot adoption, separations increase with a smaller magnitude one year later. Overall, employment effects are modestly positive and strongest for medium-qualified women. We find no adverse employment effects for female workers in any of our broad qualification groups.

Abstract
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.

Abstract
Micro-data on robots have been very sparse in Germany so far. Consequently, a dedicated section has been introduced in the IAB Establishment Panel 2019 that includes questions on the number and type of robots used. This article describes the background and development of the survey questions, provides information on the quality of the data, possible checks and steps of data preparation. The resulting data is aggregated on industry level and compared with the frequently used robot data by the International Federation of Robotics (IFR) which contains robot supplier information on aggregate robot stocks and deliveries.