  Granular geographic data present new opportunities to understand how
neighborhoods are formed, and how they influence politics. At the same time,
the inherent subjectivity of neighborhoods creates methodological challenges in
measuring and modeling them. We develop an open-source survey instrument that
allows respondents to draw their neighborhoods on a map. We also propose a
statistical model to analyze how the characteristics of respondents and local
areas determine subjective neighborhoods. We conduct two surveys: collecting
subjective neighborhoods from voters in Miami, New York City, and Phoenix, and
asking New York City residents to draw a community of interest for inclusion in
their city council district. Our analysis shows that, holding other factors
constant, White respondents include census blocks with more White residents in
their neighborhoods. Similarly, Democrats and Republicans are more likely to
include co-partisan areas. Furthermore, our model provides more accurate
out-of-sample predictions than standard neighborhood measures.
