On your mark, get set, go: A multilevel analysis of racial residential segregation in U.S. metropolitan areas

Residential segregation research has largely proceeded along two separate tracks: aggregate-level analyses that predict segregation scores with metropolitan characteristics, and household-level studies that model locational attainments using individual attributes. This study bridges these traditions by applying a multilevel meta-regression framework to examine how metropolitan-level contexts shape White–Black, White–Latino, and White–Asian residential segregation patterns across 25 U.S. metropolitan areas. Using previously estimated coefficients from household-level locational attainment models reported in Crowell and Fossett (2022) as dependent variables in a two-step meta regression with random effects, and metropolitan-level characteristics from the 2008–2012 American Community Survey and 2010 Decennial Census as level-2 predictors, we assess how contextual factors both directly influence segregation and moderate returns on household resources such as income, education, and nativity. Our findings reveal that the locus of White locational attainment advantage varies across group comparisons. For White–Black segregation, advantage is overwhelmingly concentrated in the regression constants, indicating that group membership itself—rather than differential returns on socioeconomic resources—drives segregation, consistent with place stratification theory. For White–Latino and White–Asian comparisons, the balance between structural group membership effects and resource returns shifts more variably across metropolitan contexts. Metropolitan characteristics also matter: regional location predicts White–Black segregation, while minoritized population growth predicts White–Latino and White–Asian segregation, consistent with group threat theory. Furthermore, we find an inverse relationship between gaps in the constants and gaps in returns on resources, suggesting that the extent to which spatial assimilation can operate depends on how deeply entrenched structural inequality already is. These findings demonstrate the value of linking micro- and macro-level dimensions of segregation to illuminate the complexity of racial stratification processes.