Racial Segregation in Metropolitan Regions: What can be Learned from a Social Interaction Approach?

Steven Farber, Nate Wessel and Jielan Xu

No uvpt6, SocArXiv from Center for Open Science

Abstract: Racial segregation is a pervasive social feature of American cities responsible for social, economic and health disparities. Conventional measures of segregation have been criticised for ignoring the spatial and temporal dynamics of everyday life, which are theorized to influence the ease of interaction between people. In this paper we explore a Social Interaction Potential based measure of racial segregation (SIP-Seg). SIP-Seg attempts to quantify the time-geographic constraints on between-group and within-group interaction opportunities based on the spatial distributions of residences, workplaces, and the daily commute. We compute SIP-Seg for all Metropolitan Statistical Areas (MSAs) in the United States, and regress them against conventional measures of segregation as well as a host of factors capturing the spatial structure of regions. Our results indicate that the relationship between zonal segregation and SIP-Seg is strong, but the strongest explanatory factors are race-disaggregated commuting distances, which explain far more of the variance than non-racial spatial structure factors. The research suggests that SIP-Seg captures a spatiotemporal dimension of segregation that is ignored by conventional measures.

Date: 2018-05-22
New Economics Papers: this item is included in nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:uvpt6

DOI: 10.31219/osf.io/uvpt6

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