Measuring and Modeling Neighborhoods

The availability of granular geographic data presents new opportunities to understand how neighborhoods are formed and how they influence attitudes and behavior. To facilitate such studies, we develop an online survey instrument for respondents to draw their neighborhoods on a map. We then propose a statistical model to analyze how the characteristics of respondents and geography, and their interactions, predict subjective neighborhoods. We illustrate the proposed methodology using a survey of 2,572 voters in Miami, New York City, and Phoenix. Holding other factors constant, White respondents tend to include census blocks with more White residents in their neighborhoods. Similarly, Democratic and Republican respondents are more likely to include co-partisan census blocks. Our model also provides more accurate out-of-sample predictions than standard distance-based neighborhood measures. Lastly, we use these methodological tools to test how demographic information shapes neighborhoods, but find limited effects from this experimental manipulation. Open-source software is available for implementing the methodology.