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. Author manuscript; available in PMC: 2023 Jun 23.
Published in final edited form as: Am Econ Rev. 2022 Sep;112(9):2992–3038. doi: 10.1257/aer.20201653

Table 3:

Mean Risk and Disparate Impact Estimates

Linear Extrapolation Quadratic Extrapolation Local Linear Extrapolation

Panel A: Mean Risk by Race (1) (2) (3)

 White Defendants 0.338 (0.007) 0.319 (0.021) 0.346 (0.014)
 Black Defendants 0.400 (0.006) 0.394 (0.021) 0.436 (0.016)
Panel B: System-Wide Disparate Impact
 Mean Across Cases 0.054 (0.002) 0.054 (0.007) 0.042 (0.006)
Panel C: Judge-Level Disparate Impact
 Mean Across Judges 0.054 (0.003) 0.054 (0.007) 0.042 (0.006)
 Std. Dev. Across Judges 0.038 (0.003) 0.037 (0.003) 0.037 (0.003)
 Fraction Positive 0.929 (0.016) 0.931 (0.036) 0.873 (0.036)

Judges 268 268 268

Notes. This table summarizes estimates of mean risk and disparate impact from different extrapolations of the variation in Figure 2. Panel A reports estimates of race-specific average misconduct risk, Panel B reports estimates of system-wide (case-weighted) disparate impact, and Panel C reports empirical Bayes estimates of summary statistics for the judge-level disparate impact prior distribution. To estimate mean risk, column 1 uses a linear extrapolation of the variation in Figure 2, while column 2 uses a quadratic extrapolation and column 3 uses a local linear extrapolation with a Gaussian kernel and a rule-of-thumb bandwidth. Robust standard errors, two-way clustered at the individual and judge level, are obtained by a bootstrapping procedure and appear in parentheses.