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A Markov model of urban evolution: Neighbourhood change as a complex process

Author

Listed:
  • Silver, Daniel
  • Silva, Thiago H

    (University of Toronto)

Abstract
This paper seeks to advance neighbourhood change research and complexity theories of cities by developing and exploring a Markov model of socio-spatial neighbourhood evolution in Toronto, Canada. First, we classify Toronto neighbourhoods into distinct groups using established geodemographic segmentation techniques, a relatively novel application in this setting. Extending previous studies, we pursue a hierarchical approach to classifying neighbourhoods that situates many neighbourhood types within the city’s broader structure. Our hierarchical approach is able to incorporate a richer set of types than most past research and allows us to study how neighbourhoods' positions within this hierarchy shape their trajectories of change. Second, we use Markov models to identify generative processes that produce patterns of change in the city’s distribution of neighbourhood types. Moreover, we add a spatial component to the Markov process to uncover the extent to which change in one type of neighbourhood depends on the character of nearby neighbourhoods. In contrast to the few studies that have explored Markov models in this research tradition, we validate the model's predictive power. Third, we demonstrate how to use such models in theoretical scenarios considering the impact on the city’s predicted evolutionary trajectory when existing probabilities of neighbourhood transitions or distributions of neighbourhood types would hypothetically change. Markov models of transition patterns prove to be highly accurate in predicting the final distribution of neighbourhood types. Counterfactual scenarios empirically demonstrate urban complexity: small initial changes reverberate throughout the system, and unfold differently depending on their initial geographic distribution. These scenarios show the value of complexity as a framework for interpreting data and guiding scenario-based planning exercises.

Suggested Citation

  • Silver, Daniel & Silva, Thiago H, 2020. "A Markov model of urban evolution: Neighbourhood change as a complex process," SocArXiv v3ua9, Center for Open Science.
    • Handle: RePEc:osf:socarx:v3ua9
    DOI: 10.31219/osf.io/v3ua9
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    References listed on IDEAS

    as
    1. Elvin K. Wyly, 1999. "Continuity and Change in the Restless Urban Landscape," Economic Geography, Taylor & Francis Journals, vol. 75(4), pages 309-338, October.
    2. Richard Harris & Ron Johnston & Simon Burgess, 2007. "Neighborhoods, Ethnicity and School Choice: Developing a Statistical Framework for Geodemographic Analysis," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 26(5), pages 553-579, December.
    3. Peter Bergman & Raj Chetty & Stefanie DeLuca & Nathaniel Hendren & Lawrence F. Katz & Christopher Palmer, 2024. "Creating Moves to Opportunity: Experimental Evidence on Barriers to Neighborhood Choice," American Economic Review, American Economic Association, vol. 114(5), pages 1281-1337, May.
    4. Galster, George C., 2019. "Making Our Neighborhoods, Making Our Selves," University of Chicago Press Economics Books, University of Chicago Press, number 9780226599854, December.
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