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.