Economic mobility varies by location across the United States. Within a neighborhood, economic mobility also varies across race. The maps and charts below illustrate these patterns.
The Opportunity Atlas is a great resource for anyone interested in studying inter-generational economic mobility across the United States. It is a collection of academic research papers investigating geographic and racial disparities in economic mobility, and a repository of the data used in the studies.
Using anonymized tax and census records, the data follows more than 20 million children born between 1978 and 1983 from the census tract where they grew up to their adult incomes in their mid-thirties. For each census tract, the data reports the average adult income percentile reached by children whose parents stood at the 25th percentile (poor families, but not the poorest). This measure of economic mobility is also provided by race and gender.
So, does location matter? For children from similar income families, where they grow up matters a lot for how much they earn in adulthood. Below I replicate a familiar map that demonstrates the extent of geographic disparity in economic mobility in detail. Counties where poor children rose furthest are blue; counties where they stayed poorest are red.
Because the Atlas reports outcomes separately by race, it can answer a deeper question: are racial disparities in income mostly due to where people live, or does the same address provide different opportunities to different children?
Each dot below is one census tract where the Atlas measured both Black and White children from 25th-percentile families. If the same neighborhood provided the same opportunities, the dots would cluster around the diagonal. They do not. Nearly the entire cloud hangs below it, these are tracts where White children grew up to out-earn their Black neighbors from families of similar income.
The researchers report that the divide is driven almost entirely by boys: “In 99% of neighborhoods in the United States, black boys earn less in adulthood than white boys who grow up in families with comparable income.” Below I repeat the same exercise for boys and girls separately.
Among girls the cloud sits closer to the line; among boys it falls well below it. Note that the cloud for girls is higher on the vertical axis than the cloud for boys, indicating higher income outcomes for girls
Below, I pool the data across all tract and plot the distributions by race. Note that the Black and Asian-American distributions barely overlap. Children of low-income Asian-American families reach the highest average ranks; Black children the lowest, with Hispanic and White children in between.
Splitting White and Black by sex confirms the pattern in the scatter above: the Black–White distance between the mean ticks is wider for boys than for girls.
Note that same tract does not mean 'same everything'. Within a tract, Black and White families at the same income percentile may still differ in factors such as wealth, schooling, and treatment by institutions. The same-tract comparison removes neighborhood differences, not all differences and this is precisely why the gap is informative. It helps identify the impact of all the other relative advantages and disadvantages that shape outcomes.
Place matters a lot, and race is a big part of the story. The same neighborhoods that send poor White children toward the middle class lead their Black neighbors toward a median ten percentiles lower. Your neighborhood is an important determinant of opportunities, but it is not the same opportunity for everyone who lives there.