  Bayesian Improved Surname Geocoding (BISG) is a ubiquitous tool for
predicting race and ethnicity using an individual's geolocation and surname.
BISG assumes that in the United States population, surname and geolocation are
independent given a particular race or ethnicity. This assumption appears to
contradict conventional wisdom including that people often live near their
relatives and others with similar demographic features. Here we demonstrate
that this independence assumption results in systematic biases for minority
subpopulations. For example, in areas with large White populations, BISG errors
are large in magnitude and tend to have the same sign for given minority
subpopulations. We introduce a simple raking-based prediction algorithm that
offers a significant improvement over BISG and we validate our algorithm on
states' voter registration lists. The proposed improvement and the inaccuracies
of BISG generalize to applications in election law, health care, finance, tech,
law enforcement and many other fields.

Applications;Methodology