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The role of neighborhood characteristics in explaining political party residential segregation

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  • Ihlanfeldt, Keith
  • Yang, Cynthia Fan

Abstract

High levels of neighborhood political residential segregation have recently been documented for the U.S. This has raised concerns, based on the argument that more politically homogeneous neighborhoods promote extremism and ideological intensity, resulting in this same extremism displayed by elected politicians. Using tens of thousands of single-family home sales from South Florida, our purpose is to examine the extent to which neighborhood observable descriptors can explain party segregation. Our results reveal significant differences between Democrat and Republican home buyers in the types of neighborhoods they choose. In comparison to Democrats, Republicans more frequently chose neighborhoods where a larger percentage of workers have short commutes, homes are on average larger in size, there are fewer restaurants and shops, population density is lower, and Hispanics are a smaller percentage of residents. These differences are found to be important in explaining neighborhood party segregation.

Suggested Citation

  • Ihlanfeldt, Keith & Yang, Cynthia Fan, 2024. "The role of neighborhood characteristics in explaining political party residential segregation," Regional Science and Urban Economics, Elsevier, vol. 105(C).
    • Handle: RePEc:eee:regeco:v:105:y:2024:i:c:s0166046224000164
    DOI: 10.1016/j.regsciurbeco.2024.103992
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    More about this item

    Keywords

    Residential choice; Neighborhood effects; Partisan differences; Housing attributes;
    All these keywords.

    JEL classification:

    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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