Abstract
Comparative segregation analysis holds the potential to provide rich insights into urban socio-spatial dynamics. However, comparisons of the levels of segregation between two, or more, cities at the same point in time can be complicated by different spatial contexts as well as ethnic, racial, and class distributions. The extent to which differences in segregation between two cities is due to differences in spatial structure or to differences in composition remains an open question. This paper develops a framework to disentangle the contributions of spatial structure and composition in carrying out comparative segregation analysis. The approach uses spatially explicit counterfactuals embedded in a Shapley decomposition. We illustrate this framework in a case study of the 50 largest metropolitan statistical areas in the U.S.
Sergio Rey
Director and Professor
My research interests include geographic information science, spatial inequality dynamics, regional science, spatial econometrics, and spatial data science.
Elijah Knaap
Associate Director & Senior Research Scientist
My research interests include urban inequality, neighborhood dynamics, housing markets, spatial data science, regional science, and housing & land policy.