Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/203667
Authors: 
Eppelsheimer, Johann
Rust, Christoph
Year of Publication: 
2019
Series/Report no.: 
Beiträge zur Jahrestagung des Vereins für Socialpolitik 2019: 30 Jahre Mauerfall - Demokratie und Marktwirtschaft - Session: Econometrics - Forecasting II No. F18-V3
Abstract: 
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 spatial sorting of workers and the entanglement of spillover and supply effects with an extensive set of time-varying fixed effects. Our estimates reveal that spillovers from highskilled workers attenuate monotonously with distance. Effects disappear after approximately 20 kilometers. Furthermore, our findings illustrate the benefits of applying functional regression to modern (spatial) economic data.
Subjects: 
Knowledge Spillovers
Human Capital Externalities
Functional Regression
Georeferenced Data
Education
Wages
JEL: 
D62
J24
J31
R10
R23
Document Type: 
Conference Paper

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