We study the sources of racial disparities in income using anonymized longitudinal data covering nearly the entire U.S. population from 1989 to 2015. We document three results. First, black Americans and American Indians have much lower rates of upward mobility and higher rates of downward mobility than whites, leading to persistent disparities across generations. Conditional on parent income, the black-white income gap is driven by differences in wages and employment rates between black and white men; there are no such differences between black and white women. Hispanic Americans have rates of intergenerational mobility more similar to whites than blacks, leading the Hispanic-white income gap to shrink across generations. Second, differences in parental marital status, education, and wealth explain little of the black-white income gap conditional on parent income. Third, the black-white gap persists even among boys who grow up in the same neighborhood. Controlling for parental income, black boys have lower incomes in adulthood than white boys in 99% of Census tracts. The few areas with small black-white gaps tend to be low-poverty neighborhoods with low levels of racial bias among whites and high rates of father presence among blacks. Black males who move to such neighborhoods earlier in childhood have significantly better outcomes. However, less than 5% of black children grow up in such areas. Our findings suggest that reducing the black-white income gap will require efforts whose impacts cross neighborhood and class lines and increase upward mobility specifically for black men.

We construct a public atlas of mean outcomes in adulthood by childhood census tract. Outcomes vary sharply across neighborhoods: For children whose parents earn $27,000, the standard deviation of mean household income in adulthood is $10,420 across tracts within counties. Only half the variation in outcomes is explained by traditional measures of neighborhood opportunity like poverty rates. Experimental and quasi-experimental estimates indicate 60 percent of the variation in outcomes across neighborhoods is driven by causal effects. We demonstrate how our statistics can be applied to better target policies to improve low-opportunity areas and help families move to affordable high-opportunity areas.