This paper applies functional regression to precise geo-coded register data to measure productivity spillovers from high-skilled workers. We use a smoothing splines estimator to model the spatial distribution of high-skilled workers as continuous curves. Our rich panel data allows us to address...

This paper analyzes human capital externalities from high-skilled workers by applying functional regression to precise geocoded register data. Functional regression enables us to describe the concentration of high-skilled workers around workplaces as continuous curves and to efficiently estimate...

We extract estimation results on the Mincer earnings function from four earlier studies and add new results from a recent dataset. We analyse differences related to differences in earnings concepts, in sampling frame and differences among studies that cannot be explained. Jointly, the studies...

This paper combines the approach by Guimarães and Portugal (2010) with the methodology of Gelbach (2015) to investigate the determinants of the least squares bias of the wage return to education. We find that disregarding individual fixed effects is highly problematic, accounting for 95% of the...

This paper uses data from the Cedefop European Skills and Jobs (ESJ) survey, a new international dataset of adult workers in 28 EU countries, to decompose the wage penalty of overeducated workers. The ESJ survey allows for integration of a rich, previously unavailable, set of factors in the...