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

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.