  U.S. metropolitan areas, particularly in the industrial Midwest and
Northeast, are well-known for high levels of racial segregation. This is
especially true where core cities end and suburbs begin; often crossing the
street can lead to physically similar, but much less ethnically diverse,
suburban neighborhood. While these differences are often visually or
"intuitively" apparent, this study seeks to quantify them using Geographic
Information Systems and a variety of statistical methods. 2016 Census block
group data are used to calculate an ethnic Herfindahl index for a set of two
dozen large U.S. cities and their contiguous suburbs. Then, a mathematical
method is developed to calculate a block-group-level "Border Disparity Index"
(BDI), which is shown to vary by MSA and by specific suburbs. Its values can be
compared across the sample to examine which cities are more likely to have
borders that separate more-diverse block groups from less-diverse ones. The
index can also be used to see which core cities are relatively more or less
diverse than their suburbs, and which individual suburbs have the largest
disparities vis-\`a-vis their core city. Atlanta and Detroit have particularly
diverse suburbs, while Milwaukee's are not. Regression analysis shows that
income differences and suburban shares of Black residents play significant
roles in explaining variation across suburbs.
