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The Spatial Decay of Human Capital Externalities : A Functional Regression Approach with Precise Geo-referenced Data

Title data

Eppelsheimer, Johan ; Jahn, Elke ; Rust, Christoph:
The Spatial Decay of Human Capital Externalities : A Functional Regression Approach with Precise Geo-referenced Data.
In: Regional Science and Urban Economics. Vol. 95 (2022) . - No. 103785.
ISSN 0166-0462
DOI: https://doi.org/10.1016/j.regsciurbeco.2022.103785

Abstract in another language

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 determined by distance. Furthermore, our rich panel data allow us to address the sorting of workers and 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 increasing distance and disappear after 25 km. Externalities from the immediate neighborhood of an establishment are twice as large as externalities from surroundings 10 km away.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: Human capital externalities; Functional regression; Geodata; Wages
Subject classification: JEL classification: C13 D62 J24 J31 R10 R12
Institutions of the University: Faculties
Faculties > Faculty of Law, Business and Economics
Faculties > Faculty of Law, Business and Economics > Department of Economics
Faculties > Faculty of Law, Business and Economics > Department of Economics > Chair Labour Economics
Faculties > Faculty of Law, Business and Economics > Department of Economics > Chair Labour Economics > Chair Labour Economics - Univ.-Prof. Dr. Elke Jahn
Result of work at the UBT: Yes
DDC Subjects: 300 Social sciences
300 Social sciences > 330 Economics
Date Deposited: 13 Jun 2022 07:08
Last Modified: 13 Jun 2022 07:08
URI: https://eref.uni-bayreuth.de/id/eprint/70051