Modeling Housing Abandonment and Demolition in a Shrinking City (Buffalo NY) from Bottom Up

In the past, we have wrote about using spatial statistics to detect clusters of housing abandonment and demolition in Buffalo, NY as a macro level for the entire city. Now, moving from the city to the household level, we (Li Yin, Robert M. Silverman and myself) have developed an agent-based model to capture the emergence of housing abandonment patterns from bottom up. 

Particularly, the model captures individual households' decision-making process with respect to housing abandonment by including factors such as the housing attributes (e.g., lot front size, building age, housing sale prices) and neighborhood characteristics (e.g., existence of abandonment properties in the neighborhood, adjacency to anchor institutions, and 311 reports). The beauty of agent-based model (of course, our model as well) lies in its ability to capture interactions between agents. Specifically, in our model, each household's decision-making on keeping their house or not can affect their neighbors' preference. Meanwhile, the city's housing policy to demolish-or-revitalize abandoned properties can also impact households' decisions. 

By modeling individual households' decisions and their interactions with other actors, our model can accurately simulate the spatial patterns of housing abandonment in Buffalo over years (2003-2012). We then used the calibrated model to test different demolition and revitalization policies to help policy-makers tackle with urban shrinkage and explore alternative policies. 

Abstract:

Demolition plans have been used to promote revitalization in America’s Rust Belt shrinking cities. However, demolition can barely keep up with abandonment in shrinking cities like Buffalo, New York. This study uses the agent-based approach to explore alternative demolition and neighborhood revitalization policies, built on previous studies on abandonment in Buffalo and other cities. We developed a spatially explicit agent-based modeling framework to simulate four demolition policy scenarios: 1) random demolition; 2) targeted demolition in the areas with the highest abandonment density and near amenities with public interests; 3) targeted demolition in the areas with the highest abandonment density and near commercial corridors, and 4) targeted demolition in the areas with the highest owner-occupied housing rates. The results of our analysis suggest that Buffalo’s approach to demolition and neighborhood revitalization resembles a policy framework that uses the demolition of residential units to stabilize commercial corridors. Under this strategy, public investments in commercial corridors are expected to trickle down to adjacent neighborhoods. However, to date, this has not been the outcome. This suggests the need to consider alternative strategies to achieve neighborhood revitalization goals. 

Full reference: 

Yin, L., Yin, F., & Silverman, R. M. (2024). Rethinking demolition plans to fight neighborhood blight in shrinking cities: Applying agent-based policy simulations. Cities, 150, 105035. Available at: https://doi.org/10.1016/j.cities.2024.105035 (pdf)

 

Using Agent-based Modeling to Capture the Emergence of Urban Shrinkage from Bottom Up 

Spatial ABM Modeling Framework: Entities, Environments, Agents' Behaviors and Interactions  

 Kernel Density Maps of Housing Abandonment under Various Demolition Policy Simulations.