Separate but Not Equal: The Uneven Cost of Residential Segregation for Network-Based Hiring

Tam Mai

Working Papers from U.S. Census Bureau, Center for Economic Studies

Abstract: This paper studies how residential segregation by race and by education affects job search via neighbor networks. Using confidential microdata from the US Census Bureau, I measure segregation for each characteristic at both the individual level and the neighborhood level. My findings are manifold. At the individual level, future coworkership with new neighbors on the same block is less likely among segregated individuals than among integrated workers, irrespective of races and levels of schooling. The impacts are most adverse for the most socioeconomically disadvantaged demographics: Blacks and those without a high school education. At the block level, however, higher segregation along either dimension raises the likelihood of any future coworkership on the block for all racial or educational groups. My identification strategy, capitalizing on data granularity, allows a causal interpretation of these results. Together, they point to the coexistence of homophily and in-group competition for job opportunities in linking residential segregation to neighbor-based informal hiring. My subtle findings have important implications for policy-making.

Date: 2024-10
New Economics Papers: this item is included in nep-ure
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https://www2.census.gov/library/working-papers/2024/adrm/ces/CES-WP-24-56.pdf First version, 2024 (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:cen:wpaper:24-56

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