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26-07-2017

Intergenerational Neighborhood Attainment and the Legacy of Racial Residential Segregation: A Causal Mediation Analysis

Author: Jeremy Pais

Published in: Demography | Issue 4/2017

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Abstract

Advances in mediation analysis are used to examine the legacy effects of racial residential segregation in the United States on neighborhood attainments across two familial generations. The legacy effects of segregation are anticipated to operate through two primary pathways: a neighborhood effects pathway and an urban continuity pathway. The neighborhood effects pathway explains why parent’s exposure to racial residential segregation during their family-rearing years can influence the residential outcomes of their children later in life. The urban continuity pathway captures the temporal consistency of the built and topographical environment in providing similar residential opportunities across generations. Findings from the Panel Study of Income Dynamics and U.S. Census data indicate that the legacy effect of racial residential segregation among black families operates primarily through the neighborhood effects that influence children growing up. For white families, there is less support for the legacy effects of segregation. The findings are supported by a comprehensive mediation analysis that provides a formal sensitivity analysis, deploys an instrumental variable, and assesses effect heterogeneity. Knowledge of the legacy of segregation moves neighborhood attainment research beyond point-in-time studies of racial residential segregation to provide a deeper understanding into the ways stratified residential environments are reproduced.

next article Does Black Socioeconomic Mobility Explain Recent Progress Toward Black-White Residential Integration?

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Researchers have known for some time that black-white residential segregation cannot be fully explained by racial disparities of human capital development alone (e.g., Taeuber and Taeuber 1965).

Median family income is not available for 1970, but the difference between the mean and median income at the census tract level is inconsequential given that the skew is minimal and income is logged.

This assumption can be extended to include the proper functional form of the specified relationships as well as the potential for mediator-mediator interactions. For this study, the linearity assumptions are met, and there is no statistical evidence of any interaction between the first generations’ neighborhood attainment and the second generations’ exposure to racial residential segregation. If these additional parametric assumptions are unreasonable, a researcher may wish to consult G-Computation methods (e.g., De Stavola et al. 2014).

Formal sensitivity analysis is an active area of research with new techniques emerging to handle multiple mediators and intermediate confounders (e.g., VanderWeele and Chiba 2014). The Imai et al. (2010) approach used here is generally applicable to common types of confounding that bias causal estimates of the indirect effects that are of primary interest in this study.

A related issue is that some metropolitan areas contain few PSID families. Thus, some MSAs may be poorly represented in the analyses. To examine whether this is an issue, I further restrict the subsample of stayers to only those PSID families living in metropolitan areas with at least 10 other PSID families.

It is possible to estimate the average direct effects (ADE) for the treated and control contrasts, but these effects are of less substantive interest here. For example, following Imai et al. (2010), ADE = d + x(α₂ + b × t + Σδ(X i)) where X i are specific values of the control variables. Σδ(X i) drops out here because all the control variables are grand-mean centered, X i = 0.

Construction of the sampling weights follows Sharkey (2008:943, footnote 6).

It is important to acknowledge that this interpretation relies on the untestable exogeneity assumption of the instrument.

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Title: Intergenerational Neighborhood Attainment and the Legacy of Racial Residential Segregation: A Causal Mediation Analysis
Author: Jeremy Pais
Publication date: 26-07-2017
Publisher: Springer US
Published in: Demography / Issue 4/2017
Print ISSN: 0070-3370
Electronic ISSN: 1533-7790
DOI: https://doi.org/10.1007/s13524-017-0597-8

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