IDEAS home Printed from https://ideas.repec.org/a/wsi/acsxxx/v28y2025i06ns0219525925400065.html
   My bibliography  Save this article

Dynamic Models Of Gentrification

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
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219525925400065
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1142/S0219525925400065?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wsi:acsxxx:v:28:y:2025:i:06:n:s0219525925400065. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/acs/acs.shtml .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.