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<p>This article examines the dynamics of urban segregation using an extended agent-based model (ABM) that integrates socio-economic constraints into Schelling’s (2006) classical framework. By incorporating rents, income levels and empirically derived neighbourhood preferences, the study examines how these factors influence patterns of segregation in urban environments. Two scenarios are explored: one based on Schelling’s original assumptions, emphasizing individual preferences for similarity, and another incorporating economic constraints reflecting real-world housing market constraints. Simulation results show that the constrained model stabilizes at lower levels of segregation and exhibits milder oscillations than the Schelling model, especially in high-density environments. Economic constraints act as natural barriers to extreme segregation, promoting more diverse neighbourhoods by limiting the mobility of households based solely on their preferences. Conversely, the Schelling model produces persistent instability in low-density scenarios and pronounced segregation in high-density ones. The results underline the importance of combining theoretical insights with empirical data to better capture the complexity of segregation. They also highlight the potential for housing policies—such as rent controls or inclusionary zoning—to mitigate segregation and promote inclusivity. This work contributes to the discourse on urban segregation by providing a&#xa0;more nuanced analytical tool for understanding and addressing segregation processes.</p>

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Modelling segregation based on surveyed neighbourhood preferences

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月21日

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  • Daniel Schubert

摘要

This article examines the dynamics of urban segregation using an extended agent-based model (ABM) that integrates socio-economic constraints into Schelling’s (2006) classical framework. By incorporating rents, income levels and empirically derived neighbourhood preferences, the study examines how these factors influence patterns of segregation in urban environments. Two scenarios are explored: one based on Schelling’s original assumptions, emphasizing individual preferences for similarity, and another incorporating economic constraints reflecting real-world housing market constraints. Simulation results show that the constrained model stabilizes at lower levels of segregation and exhibits milder oscillations than the Schelling model, especially in high-density environments. Economic constraints act as natural barriers to extreme segregation, promoting more diverse neighbourhoods by limiting the mobility of households based solely on their preferences. Conversely, the Schelling model produces persistent instability in low-density scenarios and pronounced segregation in high-density ones. The results underline the importance of combining theoretical insights with empirical data to better capture the complexity of segregation. They also highlight the potential for housing policies—such as rent controls or inclusionary zoning—to mitigate segregation and promote inclusivity. This work contributes to the discourse on urban segregation by providing a more nuanced analytical tool for understanding and addressing segregation processes.