In recent years, Raj Chetty has become economist-famous for cataloging American inequality, assembling enormous data sets showing which Americans tend to get ahead. More to the point, his work shows where Americans tend to get ahead. Chetty, a Harvard economics professor, has focused on how where one grows up shapes one’s economic prospects.

Chetty’s research demonstrates just how unevenly “upward mobility”—basically, people’s ability to earn more money than their parents did—is dispersed throughout the country. The following visual, for instance, shows the average earnings at age 35 of people raised in various regions to parents who were in the 25th percentile of income; the areas shaded in blue offer more upward mobility to children born there, while the areas shaded in red offer less.

But Chetty and his research collaborators have gotten much more granular than that. Those same reds and blues, it turns out, exist on the level of the city block. Consider the large disparities in average earnings for people born into low-income black families and raised in different, but nearby, parts of Brooklyn’s Brownsville neighborhood. (Each rectangle represents a city block.)

Huge gaps in economic prospects, in other words, frequently exist across very short distances. And it’s a bit jarring just how short those distances can be. “Poverty rates that are more than about half a mile away from your house are essentially completely irrelevant in predicting your own outcomes,” Chetty told an audience at the Aspen Ideas Festival, co-hosted by the Aspen Institute and The Atlantic. Which is to say, a high rate of poverty in the area immediately surrounding one’s home can be stifling, even if a “higher opportunity” neighborhood with great schools is only a short distance away.

Read more: Why inequality matters

Chetty said that this half-mile figure can be viewed as both encouraging and discouraging. It’s discouraging in the sense that a straightforward, one-size-fits-all nationwide policy would be unlikely to address neighborhood-specific disparities—something more locally tailored is probably in order.