Replication data for: Implementing Anti-discrimination Policies in Statistical Profiling Models

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Project Citation:

Pope, Devin G., and Sydnor, Justin R. Replication data for: Implementing Anti-discrimination Policies in Statistical Profiling Models. Nashville, TN: American Economic Association [publisher], 2011. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-10-13. https://doi.org/10.3886/E114766V1

Project Description

Summary: 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)

Scope of Project

JEL Classification:
      C53 Forecasting Models; Simulation Methods
      J15 Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination
      J65 Unemployment Insurance; Severance Pay; Plant Closings
      J71 Labor Discrimination

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Published Versions

V1 [2019-10-13]

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