Under the Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA) of 1996, individuals convicted of drug-related felonies were permanently banned from receiving welfare and food stamps. Since then, over 30 states have opted out of the federal ban. In this paper, I estimate the impact of public assistance eligibility on recidivism by exploiting both the adoption of the federal ban and subsequent passage of state laws that lifted the ban. Using administrative prison records on five million offenders and a triple-differences research design, I find that public assistance eligibility for drug offenders reduces one-year recidivism rates by 10 percent.

Human decision-makers frequently override the recommendations generated by predictive algorithms, but it is unclear whether these discretionary overrides add valuable private information or reintroduce human biases and mistakes. We develop new quasi-experimental tools to measure the impact of human discretion over an algorithm on the accuracy of decisions, even when the outcome of interest is only selectively observed, in the context of bail decisions. We find that 90% of the judges in our setting underperform the algorithm when they make a discretionary override, with most making override decisions that are no better than random. Yet the remaining 10% of judges outperform the algorithm in terms of both accuracy and fairness when they make a discretionary override. We provide suggestive evidence on the behaviour underlying these differences in judge performance, showing that the high-performing judges are more likely to use relevant private information and are less likely to overreact to highly salient events compared to the low-performing judges.

We study the effects of Secure Communities, an immigration enforcement program that dramatically increased interior removals of Hispanic noncitizens from the United States, on participation in means-tested social insurance programs among co-ethnic citizens. Exploiting county-level variation in the roll-out of enforcement together with its ethnic specificity, we find that Hispanic-headed citizen households significantly reduced their participation in two large federal safety net programs. Our results are most consistent with network effects that propagate fear through minority communities rather than stigma or lack of benefit information.

This article develops a new test for identifying racial bias in the context of bail decisions—a high-stakes setting with large disparities between white and black defendants. We motivate our analysis using Becker’s model of racial bias, which predicts that rates of pretrial misconduct will be identical for marginal white and marginal black defendants if bail judges are racially unbiased. In contrast, marginal white defendants will have higher rates of misconduct than marginal black defendants if bail judges are racially biased, whether that bias is driven by racial animus, inaccurate racial stereotypes, or any other form of bias. To test the model, we use the release tendencies of quasi-randomly assigned bail judges to identify the relevant race-specific misconduct rates. Estimates from Miami and Philadelphia show that bail judges are racially biased against black defendants, with substantially more racial bias among both inexperienced and part-time judges. We find suggestive evidence that this racial bias is driven by bail judges relying on inaccurate stereotypes that exaggerate the relative danger of releasing black defendants.

We show that intergenerational mobility changed rapidly by race and class in recent decades in the United States and study the causal mechanisms underlying those changes. Between the 1978 and 1992 birth cohorts, earnings increased for white children from high-income families relative to white children from low-income families, increasing earnings gaps by parental income (class) by 30%. Earnings increased for Black children at all parental income levels, reducing white-Black earnings gaps for children from low-income families by 30%. Class gaps grew and race gaps shrank similarly for nonmonetary outcomes such as educational attainment, standardized test scores, and mortality rates. Using a quasi-experimental design, we show that the divergent trends in economic mobility were caused by differential changes in childhood environments, as proxied by parental employment rates, in local communities defined by race, class, and childhood county. Outcomes improve across birth cohorts for children who grow up in communities with increasing parental employment rates, with larger effects for children who move to such communities at younger ages. Children’s outcomes are most strongly related to the parental employment rates of peers they are more likely to interact with, such as those in their own birth cohort, suggesting that the relationship between children’s outcomes and parental employment rates is mediated by social interaction.

This paper estimates the effect of Chapter 13 bankruptcy protection on financial health using a new data set linking bankruptcy filings to credit bureau records. Our empirical strategy uses the leniency of randomly assigned judges as an instrument for Chapter 13 protection. We find that Chapter 13 protection decreases an index measuring adverse financial events such as civil judgments and repossessions by 0.323 standard deviations and increases the probability of being a homeowner by 13.2 percentage points. Chapter 13 protection has little impact on open unsecured debt but decreases the amount of debt in collections by $1,333.

Over 20 percent of prison and jail inmates in the United States are currently awaiting trial, but little is known about the impact of pretrial detention on defendants. This paper uses the detention tendencies of quasi-randomly assigned bail judges to estimate the causal effects of pretrial detention on subsequent defendant outcomes. Using data from administrative court and tax records, we find that pretrial detention significantly increases the probability of conviction, primarily through an increase in guilty pleas. Pretrial detention has no net effect on future crime, but decreases formal sector employment and the receipt of employment- and tax-related government benefits. These results are consistent with (i) pretrial detention weakening defendants' bargaining positions during plea negotiations and (ii) a criminal conviction lowering defendants' prospects in the formal labor market.

A long-standing and influential view in U.S. correctional policy is that “nothing works” when it comes to rehabilitating incarcerated individuals. We revisit this hypothesis by studying an innovative law-enforcement-led program launched in the county jail of Flint, MI: Inmate Growth Naturally and Intentionally through Education (IGNITE). We develop an instrumental variables approach to estimate the effects of IGNITE exposure, leveraging quasi-random court delays that cause individuals to spend more time in jail before and after the program’s launch. Holding time in jail fixed, we find that one additional month of IGNITE exposure reduces weekly misconduct in jail by 25% and three-month recidivism by 24%, with the recidivism effects growing over time. Surveys of staff and community members, along with administrative test-score records and within-jail text messages, suggest that cultural change and improved literacy and numeracy scores are contributing mechanisms.