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A simple, statistically robust test of discrimination.

Johann D Gaebler1, Sharad Goel2

  • 1Department of Statistics, Harvard University, Cambridge, MA 02138.

Proceedings of the National Academy of Sciences of the United States of America
|March 4, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a new statistical method to detect discrimination. When two common tests agree, they reliably identify bias, revealing widespread racial discrimination in California police stops.

Keywords:
benchmark testsinframarginalitymonotone likelihood ratio propertyoutcome tests

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Area of Science:

  • Social Sciences
  • Statistics
  • Criminology

Background:

  • Observational studies of discrimination commonly use benchmark or outcome tests.
  • These individual tests have statistical limitations and can incorrectly suggest discrimination.

Purpose of the Study:

  • To develop a statistically robust method for detecting discrimination.
  • To address the limitations of existing benchmark and outcome tests.

Main Methods:

  • Proving a statistical guarantee: under a nonparametric assumption, at least one of two common tests for discrimination must be correct.
  • Developing a hybrid test where agreement between benchmark and outcome tests guarantees correct conclusions.
  • Empirically validating the assumption in lending, education, and criminal justice domains.
  • Assessing the hybrid test's robustness to assumption violations.

Main Results:

  • The hybrid test provides a strong statistical guarantee for detecting discrimination when benchmark and outcome tests agree.
  • The underlying assumption for the hybrid test holds approximately in key societal domains.
  • The hybrid test is robust to moderate violations of the assumption.
  • Analysis of 2.8 million California police stops revealed evidence of widespread racial discrimination.

Conclusions:

  • The novel hybrid statistical approach reliably detects discrimination.
  • The findings provide strong evidence of racial discrimination in California policing.