Prior research has suggested that children living in a disadvantaged neighborhood have lower achievement test scores, but these studies typically have not estimated causal effects that account for neighborhood choice. Recent studies used propensity score methods to account for the endogeneity of neighborhood exposures, comparing disadvantaged and nondisadvantaged neighborhoods. We develop an alternative propensity function approach in which cumulative neighborhood effects are modeled as a continuous treatment variable. This approach offers several advantages. We use our approach to examine the cumulative effects of neighborhood disadvantage on reading and math test scores in Los Angeles. Our substantive results indicate that recency of exposure to disadvantaged neighborhoods may be more important than average exposure for children’s test scores. We conclude that studies of child development should consider both average cumulative neighborhood exposure and the timing of this exposure.
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The R and Stata programs used to implement these procedures are provided in Online Resource 2.
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This research began when all authors were affiliated with the California Center for Population Research (CCPR) at UCLA. We greatly appreciate support from CCPR under NICHD Center Grant P2C-HD041022 and from NICHD Grant R25HD076814. It is also partially supported by the National Science Foundation (NSF, SES-1357619, IIS-1546259) and the NICHD Grant R21HD075714. We are also grateful for assistance from Christine Peterson at RAND and Rachel Veerman at UCLA.
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Hicks, A.L., Handcock, M.S., Sastry, N. et al. Sequential Neighborhood Effects: The Effect of Long-Term Exposure to Concentrated Disadvantage on Children’s Reading and Math Test Scores. Demography 55, 1–31 (2018). https://doi.org/10.1007/s13524-017-0636-5
- Child Development
- Residential histories
- Propensity function models