Deep IV in Law

This Element analyses real-world trial courts data with state-of-the-art machine learning and causal inference methods.

This Element explores the use of high-dimensional instrumental variables to estimate the influence between US Circuit Courts' decisions on criminal appeals and sentence lengths imposed by US District Courts.Do US Circuit Courts' decisions on criminal appeals influence sentence lengths imposed by US District Courts? This Element explores the use of high-dimensional instrumental variables to estimate this causal relationship. Using judge characteristics as instruments, this Element implements two-stage models on court sentencing data for the years 1991 through 2013. This Element finds that Democratic, Jewish judges tend to favor criminal defendants, while Catholic judges tend to rule against them. This Element also finds from experiments that prosecutors backlash to Circuit Court rulings while District Court judges comply. Methodologically, this Element demonstrates the applicability of deep instrumental variables to legal data.