The Impacts of Neighborhoods on Intergenerational Mobility II: County-Level Estimates

Working Paper: NBER ID: w23002

Authors: Raj Chetty; Nathaniel Hendren

Abstract: We estimate the causal effect of each county in the U.S. on children's incomes in adulthood. We first estimate a fixed effects model that is identified by analyzing families who move across counties with children of different ages. We then use these fixed effect estimates to (a) quantify how much places matter for intergenerational mobility, (b) construct forecasts of the causal effect of growing up in each county that can be used to guide families seeking to move to opportunity, and (c) characterize which types of areas produce better outcomes. For children growing up in low-income families, 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%. There is substantial local area variation in children's outcomes: for example, growing up in the western suburbs of Chicago (DuPage County) would increase a given child's income by approximately 30% relative to growing up in Cook County. Areas with less concentrated poverty, less income inequality, better schools, a larger share of two-parent families, and lower crime rates tend to produce better outcomes for children in poor families. Boys' outcomes vary more across areas than girls' outcomes, and boys have especially negative outcomes in highly segregated areas. One-fifth of the black-white income gap can be explained by differences in the counties in which black and white children grow up. Areas that generate better outcomes have higher house prices on average, but our approach uncovers many “opportunity bargains” – places that generate good outcomes but are not very expensive.

Keywords: intergenerational mobility; neighborhood effects; economic outcomes

JEL Codes: H0; J0; R0


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
childhood exposure to a one standard deviation (SD) better county (I14)child's income in adulthood (J13)
growing up in DuPage County, IL (J79)child's income (J13)
neighborhood characteristics (lower poverty concentration, less income inequality, better schools, lower crime rates) (R23)children's economic outcomes (J13)
neighborhood quality (R23)boys' outcomes (I24)
differences in counties (H73)black-white income gap (D31)

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