Highlighted Publications




 

Filippucci, Gal, and Schief (2026) examine how much generative artificial intelligence is likely to increase productivity across the U.S. economy and whether uneven gains across industries will reduce overall growth. They combine data on AI task exposure, industry employment patterns, AI adoption rates, and U.S. input-output tables covering 65 industries. They estimate that AI could increase aggregate total factor productivity growth by about 0.87 percentage points annually o

Lawson and Sass (2026) study how teachers’ effectiveness changed when schools shifted from in-person to remote instruction. They ask whether the move to online learning altered relative teacher performance and which teacher traits predicted success. They analyze matched student–teacher administrative data from three large metro-Atlanta districts, using fall-to-winter math and reading test score growth for grades K–8. They find that variation in teacher effectiveness increased

Singh, Zhou, Curtis, Maher, and Dumuid (2026) examined how after-school social media use is associated with adolescent well-being across development. They asked whether the relationship is nonlinear and whether it differs by age and sex. The study analyzed data from the South Australian Wellbeing and Engagement Collection, including 100,991 students (173,533 observations) from grades 4–12 between 2020 and 2022. They found a U-shaped pattern: moderate users generally showed th

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