  Bayesian Improved Surname Geocoding (BISG) is a ubiquitous tool for
predicting race and ethnicity using an individual's geolocation and surname.
Here we demonstrate that statistical dependence of surname and geolocation
within racial/ethnic categories in the United States results in biases for
minority subpopulations, and we introduce a raking-based improvement. Our
method augments the data used by BISG--distributions of race by geolocation and
race by surname--with the distribution of surname by geolocation obtained from
state voter files. We validate our algorithm on state voter registration lists
that contain self-identified race/ethnicity.
