Highlighted Publications




 

Orr (2026) asks whether evidence-based policy clearinghouses give reliable advice to local policymakers when program impacts vary across places. He examines data from six large multisite randomized controlled trials in education and youth programs, drawing on site-level impact estimates and cross-site variation reported in prior studies. Using a Bayesian model, he evaluates how often a clearinghouse rule based on statistically significant average effects leads to correct loca

Wilk, Deza, Hodge, and Danagoulian (2026) ask whether recreational marijuana laws change adults’ eating habits and physical activity. They examine grocery purchase data from the NielsenIQ Consumer Panel, self-reported exercise from the Behavioral Risk Factor Surveillance System, and time-use data from the American Time Use Survey. They find that recreational marijuana laws increase spending on junk food by about 1.8 percent and raise the likelihood that a grocery trip include

Jacobs et al. (2026) ask whether collaborative robots (cobots) can be used to raise productivity while preserving jobs, rather than displacing workers. They examine existing research, industry case examples, and prior empirical studies on automation, worker safety, ergonomics, and labor markets, rather than analyzing a new dataset. They find that cobots tend to automate specific tasks instead of whole jobs, reducing physical strain and workplace injuries while increasing outp

Agan et al. (2025) ask whether clearing or sealing criminal records improves employment outcomes. They examine linked administrative court records from Maryland, New Jersey, Pennsylvania, and Texas merged with IRS tax data on earnings, employment, and gig work. They find that criminal charges—both convictions and non-convictions—are followed by large and persistent employment declines. However, removing records through Fair Credit Reporting Act rules or Clean Slate laws has l