Author
Listed:
- GIOVANNI MAURO
(ISTI-CNR, Pisa, Italy2Scuola Normale Superiore, Pisa, Italy3Department of Computer Science, University of Pisa, Pisa, Italy4IMT School for Advanced Studies, Lucca, Italy)
- NICOLA PEDRESCHI
(Mathematical Institute, University of Oxford, UK)
- RENAUD LAMBIOTTE
(Mathematical Institute, University of Oxford, UK)
- LUCA PAPPALARDO
(ISTI-CNR, Pisa, Italy2Scuola Normale Superiore, Pisa, Italy)
Abstract
The phenomenon of gentrification of an urban area is characterized by the displacement of lower-income residents due to rising living costs and an influx of wealthier individuals. This study presents an agent-based model that simulates urban gentrification through the relocation of three income groups — low, middle, and high — driven by living costs. The model incorporates economic and sociological theories to generate realistic neighborhood transition patterns. We introduce a temporal network-based measure to track the outflow of low-income residents and the inflow of middle- and high-income residents over time. Our experiments reveal that high-income residents trigger gentrification and that our network-based measure consistently detects gentrification patterns earlier than traditional count-based methods, potentially serving as an early detection tool in real-world scenarios. Moreover, the analysis highlights how city density promotes gentrification. This framework offers valuable insights for understanding gentrification dynamics and informing urban planning and policy decisions.
Suggested Citation
Giovanni Mauro & Nicola Pedreschi & Renaud Lambiotte & Luca Pappalardo, 2025.
"Dynamic Models Of Gentrification,"
Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 28(06), pages 1-21, September.
Handle:
RePEc:wsi:acsxxx:v:28:y:2025:i:06:n:s0219525925400065
DOI: 10.1142/S0219525925400065
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