The Wrong Side(s) of the Tracks: Estimating the Causal Effects of Racial Segregation on City Outcomes
The strong negative correlation between a city’s level of residential racial segregation and its outcomes, particularly for black residents, is well-established. The interpretation of this relationship, however, is confounded by the possibility that cities that have other negative characteristics tend also to be more segregated, leading to omitted variable bias. I address this concern by using the placement of railroad tracks in the 19th century as an instrument for a city’s ability to segregate upon the arrival of significant African-American populations in the 20th century. I show that, conditional on actual quantity of railroad track, variation in the way tracks were configured predicts the level of segregation a city experienced after the Great Migration. Using two-stage least squares analysis, I find that more segregated cities have worse outcomes for high- and low-skilled blacks and for high-skilled whites, but better outcomes for low-skilled whites. Ordinary least squares estimates appear to bias the estimated effects of segregation on low-skilled outcomes downward, while biasing estimates of high-skilled white outcomes upwards, perhaps because endogenous segregation is related to broader inequality. I develop a model to help identify separate effects of randomized segregation on the production of human capital versus general equilibrium sorting by type. Using data on migration, I find that more segregated cities are in less demand and that the benefits of segregation to low-skilled whites do not result from sorting. The negative relationship of randomized segregation with the outcomes of other groups, however, may be at least partly the result of general equilibrium sorting of these groups away from segregated cities.
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