Measuring Income Mixing and Inequality in North Carolina

The Center for Urban & Regional Studies at the University of North Carolina Chapel Hill is thrilled to announce the launch of our new blog, Urban 2 Point 0. Focusing on urban issues relevant to North Carolina and beyond, Urban 2 Point 0 will present easily digestible data analysis complemented by infographics, maps, and other visuals. In our first series of posts, we’ll look at income mixing across neighborhoods in North Carolina’s three largest metro areas:  Charlotte, the Triangle (Raleigh-Durham), and the Triad (Greensboro and Winston-Salem). We hope to show not only the level of mixing within each metro, but also income inequality across neighborhoods—that is, where poor or wealthy households are concentrated.


North Carolina is home to some of the fastest-growing cities in the nation (click image below for link to interactive map). Between 2000 and 2012, the Raleigh metro area grew faster than any large city, while Charlotte was close behind, ranking 5th. Largely due to its growing cities, North Carolina’s population exceeded the 10 million mark in 2015.

Click on the map to interact with it.

With this growth has come development pressures—especially for affordable housing—as cities struggle to balance growth and affordability while maintaining what some view as communities’ unique character. While some cities—like Raleigh—have set aside funds to develop affordable housing, others have opposed efforts to increase density or construct rental units. This opposition will likely increase isolation of lower-income households, who are unable to afford larger homes.

The importance of mixed-income communities

For many policy-makers and city planners, creating mixed-income communities is a crucial policy goal. Many have argued that mixed-income neighborhoods allow for middle-class residents to serve as role models for low-income families. Middle class neighbors can connect low-income residents to jobs, and living in wealthier areas may allow children in lower-income families to attend better schools—which many believe is critical to improving children’s economic prospects.

Both cities and the federal government have sought to increase income mixing. In the 1990s and 2000s, over 250 public housing developments were demolished and replaced with mixed-income developments in through a program known as HOPE VI. Further, many cities have adopted policies to encourage income mixing—like mandating that a certain percent of new units are affordable, using fees charged to developers or issuing bonds to fund affordable housing, and modifying zoning codes.

While creating mixed-income communities appears great on the surface, they frequently do not function as planned. It appears that lower-income and wealthier families don’t interact often, thus calling into question whether middle-class households are serving as role models. Even worse, in some New York City apartment buildings where certain apartments are affordable, developers have barred low-income residents from certain amenities, like gyms and individual storage lockers.

However, perhaps the greatest benefit of mixed-income communities is what they prevent: neighborhoods of concentrated poverty, which typically have high crime rates, poor performing schools, and other social problems. Raj Chetty and his colleagues recently found that children who moved to less-poor neighborhoods earned more as adults than those who did not move—thus suggesting that growing up in a mixed-income (or, at least, less-poor) neighborhood can reduce rates of intergenerational poverty.

Measuring income mixing and inequality

To measure the amount of income mixing in neighborhoods, we drew on U.S. Census data to calculate the percent of households in four income categories:

  • earning under $25,000 a year;
  • earning between $25,000 and $49,999 a year;
  • earning between $50,000 and $99,999 a year;
  • earning over $100,000 a year.

We use the Simpson Index to calculate the level of income mixing in each neighborhood. Put simply, the Simpson index is the chance that, if you selected two people at random, they would be in different groups. For example, if 5 boys and 5 girls were in a classroom, the Simpson Index would be 0.5 (or 50%). If there were 8 boys and 2 girls, the Simpson Index would be 0.36 (36%)—it’s lower because the classroom is less diverse.

Areas of low mixing may have a preponderance of either low- or high-income households (they could also have a lot of middle-class households). Because of this, we also include the ratio of wealthy households (those earning over $100,000) divided by those lower-income households (those earning under $25,000). This ratio allows us to measure income inequality—that is, if lower- or upper-income households are concentrated in a particular neighborhood.

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