The Spatial Decay of Human Capital Externalities - A Functional Regression Approach with Precise Geo-Referenced Data
"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 estima...
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Published in | IDEAS Working Paper Series from RePEc |
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Main Authors | , |
Format | Paper |
Language | English |
Published |
St. Louis
Federal Reserve Bank of St. Louis
01.01.2020
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Subjects | |
Online Access | Get full text |
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Summary: | "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 a spillover function that depends on distance. Furthermore, our rich panel data allow us to address the sorting of workers and to disentangle human capital externalities from supply effects by using an extensive set of time-varying fixed effects. Our estimates reveal that human capital externalities attenuate with distance and disappear after 15 kilometers. Externalities from the immediate neighborhood are twice as large as those from surroundings ten kilometers away." (Author's abstract, IAB-Doku) ((en)) |
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