Identifying Optimal City Size by Considering Inverse U-Shaped Relationship Between Population and GDP

Anushree Konar and Sabyasachi Tripathi

MPRA Paper from University Library of Munich, Germany

Abstract: Identifying the optimal population size at which cities maximize economic benefits while minimizing congestion and pollution is a challenge. This research explores the optimal city size by examining the relationship between population and economic performance, measured by city GDP. Using data from OECD regions for about 562 cities, the analysis employs a quadratic regression model to test an inverse U-shaped relationship between city population and GDP in 2020. The empirical results show that cities initially experience economic growth as populations increase, but after a certain point (8.85 million), the benefits diminish due to congestion and pollution. The study concludes that an optimal city size exists, balancing the advantages of agglomeration with the costs of urban expansion. Additionally, population density, territorial fragmentation, working-age population, and built-up area positively affect city GDP, whereas air pollution negatively impacts it. Finally, several policies are recommended for sustainable urban development and efficient resource allocation.

Keywords: Urban growth; optimal city size; population size; economic measurement; OECD cities. (search for similar items in EconPapers)
JEL-codes: R0 R1 R11 R12 (search for similar items in EconPapers)
Date: 2025-05-03
New Economics Papers: this item is included in nep-ene and nep-geo
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/124673/1/MPRA_paper_124673.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:124673

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().