This editorial introduces the nine papers included in this issue of Spatial Economic Analysis (SEA). The papers in this issue study how urban features influence the spatial economy and the mechanisms taking place in cities. The starting point is the importance of agglomerations in the spatial economy and what happens in cities to influence economic and social outcomes at local and wider scales. Specifically, the papers focus on the growth impact of cities that depend on network externalities; how the shape of cities influences migration and growth; the factors that influence the liveability of neighbourhoods; the influence of the urban structure on migration decisions; how external shocks and the possibility to work from home can affect people’s dwelling decisions; and the factors determining the occupancy of multi-family apartments. Furthermore, novel methodologies are presented in this issue in the estimation of the factors determining rent, such as new machine learning algorithms and spatiotemporal hedonic modelling using distributional regression models and Bayesian estimators. In all urban contexts, neighbourhood spillover effects are considered and taken into account in the papers included in the issue.

The urban dimension in spatial development: contributions from spatial economics

Fratesi, Ugo;
2025-01-01

Abstract

This editorial introduces the nine papers included in this issue of Spatial Economic Analysis (SEA). The papers in this issue study how urban features influence the spatial economy and the mechanisms taking place in cities. The starting point is the importance of agglomerations in the spatial economy and what happens in cities to influence economic and social outcomes at local and wider scales. Specifically, the papers focus on the growth impact of cities that depend on network externalities; how the shape of cities influences migration and growth; the factors that influence the liveability of neighbourhoods; the influence of the urban structure on migration decisions; how external shocks and the possibility to work from home can affect people’s dwelling decisions; and the factors determining the occupancy of multi-family apartments. Furthermore, novel methodologies are presented in this issue in the estimation of the factors determining rent, such as new machine learning algorithms and spatiotemporal hedonic modelling using distributional regression models and Bayesian estimators. In all urban contexts, neighbourhood spillover effects are considered and taken into account in the papers included in the issue.
2025
cities
liveability
rent
Spatial economics
urban development
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1300265
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