In July, I showed that an otherwise careful group of researchers at the Othering and Belonging Institute were using a measure of statistical racial segregation that confounds diversity with segregation. Briefly, regions with more variety in the racial makeup of their neighborhoods will show up as statistically “segregated.” Regions where all neighborhoods are pretty similar will show up as statistically “integrated.” To their credit, the study authors corresponded with me at length and adjusted their Technical Appendix to emphasize limitations that I had pointed out. Today, Mark Zandi, Dante DeAntonio, Kwame Donaldson, and Matt Colyar of Moody’s Analytics released a much less careful study purporting to show the “macroeconomic benefits of racial integration.” But if one were to make the mistake of taking their study at all seriously it would lead one to the opposite conclusion: mostly-white counties do better economically. They discovered white privilege and mislabeled it “integration.” (When economists talk about “segregation” statistically, they mean differences in racial proportions across neighborhoods. This is not the same as the de jure segregation regime imposed in the American South. It’s not even the de facto segregation that persists in some neighborhoods today.) The easiest way to see Zandi et al’s mistake is to work backwards from the table of county results they (helpfully) published. The most integrated county in America, in their analysis, is Kennebec County, Maine. It’s 94.6% white. The rest of the most-integrated counties are similarly pallid – with the exception of Webb County, Texas, which is 95% Hispanic. In each of these counties, integration is a mathematical product of the lack of diversity. With hardly any minorities, hardly any neighborhood can diverge from the dominant group. These extreme counties aren’t an accident. Whereas most researchers treat metropolitan areas together, Zandi’s team worked with counties. Several of their […]
