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Exploring the global and local patterns of income segregation in Toronto, Canada: A multilevel multigroup modeling approach

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  • Matthew Quick

    (7864Arizona State University, United States)

  • Nick Revington

Abstract

Residential income segregation is a spatial manifestation of social inequality and is an important factor that influences access to resources, services, and amenities. In general, past research analyzing income segregation has applied index-based methods to describe the separation of low-income households at one spatial scale; however, existing studies have not yet considered how income segregation varies across multiple income classes, spatial scales, and local contexts. This study applies a multilevel multigroup modeling approach to explore the global and local patterns of income segregation between dissemination areas (micro-scale), census tracts (meso-scale), and neighborhoods (macro-scale) in Toronto, Canada. A global model that estimates the overall multiscale segregation of five income classes finds that the most affluent families had the highest levels of segregation and that the segregation of all income classes was strongest at the macro- and micro-scales. A local model that allows the micro-scale segregation measures to vary geographically shows that higher-income families were less segregated in the city center than in the inner suburbs, that middle-income families were highly segregated in areas serviced by public transit, and that almost all income classes had high levels of segregation in disadvantaged neighborhoods prioritized for investment by local policymakers. The methodological and substantive contributions of this study for understanding the complex patterns of income segregation are discussed.

Suggested Citation

  • Matthew Quick & Nick Revington, 2022. "Exploring the global and local patterns of income segregation in Toronto, Canada: A multilevel multigroup modeling approach," Environment and Planning B, , vol. 49(2), pages 637-653, February.
    • Handle: RePEc:sae:envirb:v:49:y:2022:i:2:p:637-653
    DOI: 10.1177/23998083211021419
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