How should statistical models used for assigning prices or eligibility be implemented when there is concern about discrimination? In many settings, factors such as race, gender, and age are prohibited. However, the use of variables that correlate with these omitted characteristics (e.g., zip codes, credit scores) is often contentious. We provide a framework to address these issues and propose a method that can eliminate proxy effects while maintaining predictive accuracy
relative to an approach that restricts the use of contentious variables outright. We illustrate the value of our proposed method using data from the Worker Profiling and Reemployment Services system. (JEL C53, J15, J65, J71)
Pope, Devin G., and Justin R. Sydnor.
"Implementing Anti-discrimination Policies in Statistical Profiling Models."
American Economic Journal: Economic Policy,
Forecasting Methods; Simulation Methods
Economics of Minorities and Races; Non-labor Discrimination
Unemployment Insurance; Severance Pay; Plant Closings