Using the Census Bureau’s surname list to improve estimates of race/ethnicity and associated disparities

By M. Elliott, P. Morrison, A. Fremont, Daniel F McCaffrey, Philip M Pantoja, N. Lurie. 2009

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Yan Zhang
2. Jiahao Chen
3. Keke Gai

Citations in the corpus

• Assessing Fair Lending Risks Using Race/Ethnicity Proxies (2018, methodology): “Elliott et al. (2009) use health plan enrollment data with reported race/ethnicity to evaluate how well the BISG method predicts race/ethnicity and find that the BISG methodology is more accurate than the geo-only or surname-only approach.”
• The Effects of Rent Control Expansion on Tenants, Landlords, and Inequality: Evidence from San Francisco (2019, unknown): “CFPB (2014) and Elliott et al. (2009) demonstrate that combining geography- and name-based information into a single proxy probability for race/ethnicity significantly outperforms traditional classification methods based on names or geography alone.”