Schelling-like model and Residential dynamics: A simulation of neighborhood segregation.
Tran, Thi Thanh Thanh
Tran, Thi Thanh Thanh
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Abstract
More than fifty years after the Fair Housing Act, American neighborhoods remain deeply segregated, suggesting that segregation is maintained through other factors rather than legal barriers. In 1971, Thomas Schelling proposed a simple model showing that even small preferences for living near similar neighbors can produce deeply divided communities over time. What makes this striking is that large-scale segregation can emerge without anyone intending it. However, Schelling's original model makes two important simplifications. First, it assumes all residents are equally free to move, ignoring the role of money. In reality, wealthier families can afford to search across distant neighborhoods, while lower-income families are often limited to nearby options. Second, the model only considers who your neighbors are, not what the neighborhood itself is like. This project builds a cellular automaton (CA) model that addresses both gaps. We introduce economic constraints that limit how far different agents can search for new homes, and we add neighborhood quality as a factor shaping relocation decisions. Together, these additions create a more realistic picture of how segregation forms and persists. We measure segregation patterns using cluster size and boundary density and tracking how they change as we adjust income distribution, neighborhood quality, and tolerance levels. Our results show that these factors significantly impact the model outcome, both independently and in combination with each other.
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Date
1/1/2026
Student Status
Graduate Student
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Poster
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Complex System & Data Science
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College of Engineering and Mathematical Sciences
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Social Science