We compare predictions from a conventional protocol-based approach to risk assessment with those based on a machine-learning approach. We first show that the conventional predictions are less accurate than, and have similar rates of negative prediction error as, a simple Bayes classifier that...

We compare predictions from a conventional protocol-based approach to risk assessment with those based on a machine-learning approach. We first show that the conventional predictions are less accurate than, and have similar rates of negative prediction error as, a simple Bayes classifier that...

Domestic abuse is a pervasive global problem. Here we analyze two approaches to reducing violent DA recidivism. One involves charging the perpetrator with a crime; the other provides protective services to the victim on the basis of a formal risk assessment carried out by the police. We use...

Previous work has documented that speaking one's native language with an accent distinct from the mainstream is associated with lower wages. In this study, we seek to estimate the causal effect of speaking with a distinctive regional accent, disentangling the effect of the accent from that of...

Among the most important changes brought about by the Personal Responsibility and Work Opportunity Reconciliation Act of 1996 (PRWORA) is the imposition of time limits. In this paper, we analyze a simple model in which a potential welfare recipient chooses how to allocate her time-limited...

Domestic abuse is a pervasive global problem. Here we analyze two approaches to reducing violent DA recidivism. One involves charging the perpetrator with a crime; the other provides protective services to the victim on the basis of a formal risk assessment carried out by the police. We use...

Domestic abuse is a pervasive global problem. Here we analyze two approaches to reducing violent DA recidivism. One involves charging the perpetrator with a crime; the other provides protective services to the victim on the basis of a formal risk assessment carried out by the police. We use...