  We use near-far matching, a technique for estimating causal relationships, to
explore whether bail causes a higher likelihood of conviction. We find evidence
of a strong causal impact. This paper was compiled as a submission to the 2017
Fairness, Accountability, and Transparency in Machine Learning (FAT ML)
workshop.
