We examine the impact of Articial Intelligence (AI) on productivity in the context of taxi drivers. The AI we study assists drivers with finding customers by suggesting routes along which the demand is predicted to be high. We find that AI improves drivers' productivity by shortening the...

Although at least 400 million people suffer from seasonal allergies worldwide, the adverse effects of pollen on "non-health" outcomes, such as cognition and productivity, are relatively understudied. Using ambulance archives from Japan, we demonstrate that high pollen days are associated with...

Classroom peers are believed to influence learning by teaching each other, and the efficacy of this teaching likely depends on classroom composition in terms of peers' ability. Unfortunately, little is known about peer-to-peer teaching because it is never observed in field studies. Furthermore,...

We evaluate the impact of government mandated proof of vaccination requirements for access to public venues and non-essential businesses on COVID-19 vaccine uptake. We find that the announcement of a mandate is associated with a rapid and significant surge in new vaccinations (more than 60%...

Staggered difference-in-differences designs are pervasive in policy evaluations but little is known about the mechanisms of policy diffusion: How and why do such policies spread across jurisdictions? In this study, we highlight the role of elections in policy diffusion in settings where...

Despite a recent and dramatic re-evaluation of the health consequences of alcohol consumption, very little is known about the effects of in utero exposure to alcohol on long-run outcomes such as later-life mortality. Here, we investigate how state by year variation in alcohol control arising...

We examine the mortality effects of a 1947 school reform in Japan, which extended compulsory schooling from primary to secondary school by as much as 3 years. The abolition of secondary school fees also indicates that those affected by the reform likely came from disadvantaged families who could...