Measuring conditional segregation: methods and empirical examples

In empirical studies of segregation it is often desirable to quantify segregation that cannot be explained by underlying characteristics. To this end, we propose a fully non-parametric method for accounting for covariates in any measure of segregation. The basic idea is that given a set of discrete characteristics, there is a certain probability that a person belongs to a particular group, which can be used to compute an expected level of segregation. We also demonstrate that a modified index of exposure has both favorable analytical features and interpretational advantages in such settings. The methods are illustrated by an application to ethnic workplace segregation in Sweden. We also show how one can use a measure of exposure to study the earnings consequences of segregation stemming from different sources.

Keywords: exposure, covariates, ethnic workplace segregation
JEL codes: C15, J15, J42