We develop new quasi-experimental tools to measure disparate impact, regardless of its source, in the context of bail decisions. We show that omitted variables bias in pretrial release rate comparisons can be purged by using the quasi-random assignment of judges to estimate average pretrial misconduct risk by race. We find that two-thirds of the release rate disparity between white and Black defendants in New York City is due to the disparate impact of release decisions. We then develop a hierarchical marginal treatment effect model to study the drivers of disparate impact, finding evidence of both racial bias and statistical discrimination.

中文翻译：

---

衡量保释决定中的种族歧视。

我们开发了新的准实验工具来衡量保释决定中不同的影响，无论其来源如何。我们表明，通过使用法官的准随机分配来估计按种族划分的平均审前不当行为风险，可以消除审前释放率比较中的遗漏变量偏差。我们发现，纽约市白人和黑人被告的释放率差异三分之二是由于释放决定的不同影响造成的。然后，我们开发了一个分层边际治疗效应模型来研究不同影响的驱动因素，寻找种族偏见和统计歧视的证据。