Cory McCartan presents "Measuring and Modeling Neighborhoods"

More granular geographical data has allowed social scientists to probe how residential neighborhoods are formed and how they influence attitudes and behavior. To facilitate such studies, we develop a survey tool that allows respondents to draw their neighborhoods on a map. We propose a hierarchical Bayesian model that can be used to analyze which factors shape their neighborhoods. We have conducted a survey of registered voters in Miami, New York City, and Phoenix, and  find that across these cities, voters are more likely to include same-race and co-partisan census blocks into their neighborhoods. We also show that our model provides more accurate out-of-sample predictions than the standard distance-based measures of neighborhoods.

This is joint work with Jacob R. Brown and Kosuke Imai.