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Scaling trajectories of cities

Urban scaling research finds that agglomeration effects—the higher-than-expected outputs of larger cities—follow robust “superlinear” scaling relations in cross-sectional data. But the paradigm has predictive ambitions involving the dynamic scaling of individual cities over many time points and expe...

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Detalles Bibliográficos
Autor principal: Keuschnigg, Marc
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6628653/
https://www.ncbi.nlm.nih.gov/pubmed/31235579
http://dx.doi.org/10.1073/pnas.1906258116
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author Keuschnigg, Marc
author_facet Keuschnigg, Marc
author_sort Keuschnigg, Marc
collection PubMed
description Urban scaling research finds that agglomeration effects—the higher-than-expected outputs of larger cities—follow robust “superlinear” scaling relations in cross-sectional data. But the paradigm has predictive ambitions involving the dynamic scaling of individual cities over many time points and expects parallel superlinear growth trajectories as cities’ populations grow. This prediction has not yet been rigorously tested. I use geocoded microdata to approximate the city-size effect on per capita wage in 73 Swedish labor market areas for 1990–2012. The data support a superlinear scaling regime for all Swedish agglomerations. Echoing the rich-get-richer process on the system level, however, trajectories of superlinear growth are highly robust only for cities assuming dominant positions in the urban hierarchy.
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spelling pubmed-66286532019-07-22 Scaling trajectories of cities Keuschnigg, Marc Proc Natl Acad Sci U S A Social Sciences Urban scaling research finds that agglomeration effects—the higher-than-expected outputs of larger cities—follow robust “superlinear” scaling relations in cross-sectional data. But the paradigm has predictive ambitions involving the dynamic scaling of individual cities over many time points and expects parallel superlinear growth trajectories as cities’ populations grow. This prediction has not yet been rigorously tested. I use geocoded microdata to approximate the city-size effect on per capita wage in 73 Swedish labor market areas for 1990–2012. The data support a superlinear scaling regime for all Swedish agglomerations. Echoing the rich-get-richer process on the system level, however, trajectories of superlinear growth are highly robust only for cities assuming dominant positions in the urban hierarchy. National Academy of Sciences 2019-07-09 2019-06-24 /pmc/articles/PMC6628653/ /pubmed/31235579 http://dx.doi.org/10.1073/pnas.1906258116 Text en Copyright © 2019 the Author(s). Published by PNAS. http://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY) (http://creativecommons.org/licenses/by/4.0/) .
spellingShingle Social Sciences
Keuschnigg, Marc
Scaling trajectories of cities
title Scaling trajectories of cities
title_full Scaling trajectories of cities
title_fullStr Scaling trajectories of cities
title_full_unstemmed Scaling trajectories of cities
title_short Scaling trajectories of cities
title_sort scaling trajectories of cities
topic Social Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6628653/
https://www.ncbi.nlm.nih.gov/pubmed/31235579
http://dx.doi.org/10.1073/pnas.1906258116
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