We develop new quasi-experimental tools to understand algorithmic discrimination and build non-discriminatory algorithms when the outcome of interest is only selectively observed. These tools are applied in the context of pretrial bail decisions, where conventional algorithmic predictions are...

Over 20 percent of prison and jail inmates in the United States are currently awaiting trial, but little is known about the impact of pre-trial detention on defendants. This paper uses the detention tendencies of quasi-randomly assigned bail judges to estimate the causal effects of pre-trial...

We study the labor market impacts of retroactively reducing felonies to misdemeanors in San Joaquin County, CA, where criminal justice agencies implemented Proposition 47 reductions in a quasi-random order, without requiring input or action from affected individuals. Linking records of...

We estimate the causal effects of parental incarceration on children's short- and long-run out-comes using administrative data from Sweden. Our empirical strategy exploits exogenous varia-tion in parental incarceration from the random assignment of criminal defendants to judges with different...