Using
Sibling Data to Estimate the Impact
of Neighborhoods on Children's Educational Outcomes
Daniel Aaronson
Abstract
Studies that attempt to measure the impact of neighborhoods on
children's outcomes are susceptible to bias because families choose
where to live. As a result, the effect of family unobservables,
such as the importance parents place on their children's welfare,
and other unobservables that are common to geographically clustered
households, may be mistakenly attributed to neighborhood influences.
Previous studies that attempt to correct for this selection bias
have used questionable instrument variables. Furthermore, results
presented in this paper suggest that IV neighborhood effect parameters
are sensitive to reasonable alterations in the instrument lists
proposed in the literature.
This paper introduces an approach based on the observation that
the latent factors associated with neighborhood choice do not vary
across siblings. Therefore, family residential changes provide a
source of neighborhoodbackground variation that is free of the family-specific
heterogeneity biases associated with neighborhood selection. Using
a sample of multiple-child families whose children are separated
in age by at least three years, I estimate family fixed effect equations
of children's educational outcomes. The fixed effect results suggest
that the impact of neighborhoods exists even when family-specific
unobservables are controlled. This finding is robust to changes
in estimation techniques, outcome measures, neighborhood measures,
variable definitions, and samples.
Daniel Aaronson, Doctoral candidate,
Department of Economics, Northwestern University
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