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Comparing the racial dissimilarity index across counties

Larger counties are more dissimilar than smaller counties

A previous FRED Blog post explained racial dissimilarity, with St. Louis City and St. Louis County as examples. In this post, we look at racial dissimilarity with a map of all US counties.

The Census Bureau identifies racial housing patterns in a county by calculating the “White to non-White racial dissimilarity index,” which ranges in value between 0 and 100. The value represents the percent of the non-Hispanic White population who would have to move from one census tract in a county to another census tract in the same county to achieve an even countywide distribution of racial groups. (See the explanations from the Census Bureau.)

The FRED map above shows racial dissimilarity data for 2021, the latest at the time of this writing. Darker colors represent more racially dissimilar counties. The grayed-out counties have only one Census tract, so it’s impossible to calculate an index for them.

At first glance, no geographical concentration of highly dissimilar counties is easily noticeable. The counties where more than half of the non-Hispanic White population would have had to change where they lived for this specific type of racial dissimilarity to disappear are, in fact, peppered across the country. However, the concentration of grayed-out areas in sparsely populated parts of the country suggests there is a relationship between the size of the population in a county and its racial dissimilarity index. We created a scatter plot of those data to look into this idea.

Each blue circle in our second data graph represents a county: Its racial dissimilarity index is on the vertical axis and its population size is plotted on the horizontal axis. The shape of the data cloud indicates that, on average, as population size increases, the racial dissimilarity index grows. In other words, Census tracts in more-populous areas are less alike than Census tracts in less-populous areas.

However, even among relatively large counties, there is remarkable variation in racial housing patterns. Consider, for example, two counties with almost exactly 400,000 residents: Genesee County, MI, and St. Charles County, MO. The racial dissimilarity index for the Michigan county (57) is more than twice as high as the racial dissimilarity index for the Missouri county (21). So population size is not all that matters here.

How this map was created: In FRED, search for “White to Non-White Racial Dissimilarity (5-year estimate) Index for St. Louis city, MO.” Click on “View Map.” To change the data units into annual growth rates, click on “Edit Map” and select “Units: Percent change from year ago.” How the scatter plot was created: We use a logarithmic scale to plot the population data because, in 2021, population across counties ranged from 2,052 persons to more than 10 million persons. Those numbers could not be easily visualized in a simple graph with linear scales.

Suggested by Diego Mendez-Carbajo.

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