The Impacts of Neighborhoods on Intergenerational Mobility: Childhood Exposure Effects and County-Level Estimates

We characterize the e↵ects of neighborhoods on children’s earnings and other outcomes in adulthood by studying more than five million families who move across counties in the U.S. Our analysis consists of two parts. In the first part, we present quasi-experimental evidence that neighborhoods a↵ect intergenerational mobility through childhood exposure e↵ects. In particular, the outcomes of children whose families move to a better neighborhood – as measured by the outcomes of children already living there – improve linearly in proportion to the time they spend growing up in that area. We distinguish the causal e↵ects of neighborhoods from confounding factors by comparing the outcomes of siblings within families, studying moves triggered by displacement shocks, and exploiting sharp variation in predicted place e↵ects across birth cohorts, genders, and quantiles. We also document analogous childhood exposure e↵ects for college attendance, teenage birth rates, and marriage rates. In the second part of the paper, we identify the causal e↵ect of growing up in every county in the U.S. by estimating a fixed e↵ects model identified from families who move across counties with children of di↵erent ages. We use these estimates to decompose observed intergenerational mobility into a causal and sorting component in each county. For children growing up in families at the 25th percentile of the income distribution, each year of childhood exposure to a one standard deviation (SD) better county increases income in adulthood by 0.5%. Hence, growing up in a one SD better county from birth increases a child’s income by approximately 10%. Low-income children are most likely to succeed in counties that have less concentrated poverty, less income inequality, better schools, a larger share of two-parent families, and lower crime rates. Boys’ outcomes vary more across areas than girls, and boys have especially poor outcomes in highly-segregated areas. In urban areas, better areas have higher house prices, but our analysis uncovers significant variation in neighborhood quality even conditional on prices. ⇤The opinions expressed in this paper are those of the authors alone and do not necessarily reflect the views of the Internal Revenue Service or the U.S. Treasury Department. This work is a component of a larger project examining the e↵ects of tax expenditures on the budget deficit and economic activity. All results based on tax data in this paper are constructed using statistics originally reported in the SOI Working Paper “The Economic Impacts of Tax Expenditures: Evidence from Spatial Variation across the U.S.,” approved under IRS contract TIRNO-12-P-00374 and presented at the O ce of Tax Analysis on November 3, 2014. We thank David Autor, Gary Chamberlain, Max Kasy, Lawrence Katz, and numerous seminar participants for helpful comments and discussions. Sarah Abraham, Alex Bell, Augustin Bergeron, Jamie Fogel, Nikolaus Hildebrand, Alex Olssen, Benjamin Scuderi, and Evan Storms provided outstanding research assistance. This research was funded by the National Science Foundation, the Lab for Economic Applications and Policy at Harvard, and Laura and John Arnold Foundation.