Firm-level stock returns differ enormously in reaction to COVID-19 news. We characterize these reactions using the Risk Factors discussions in pre-pandemic 10-K filings and two text-analytic approaches: expert-curated dictionaries and supervised machine learning (ML). Bad COVID-19 news lowers...

We measure the behavior of 1,114 CEOs in six countries parsing granular CEO diary data through an unsupervised machine learning algorithm. The algorithm uncovers two distinct behavioral types: “leaders” and “managers”. Leaders focus on multi-function, high-level meetings, while managers...

The pandemic catalyzed an enduring shift to remote work. To measure and characterize this shift, we examine more than 250 million job vacancy postings across five English-speaking countries. Our measurements rely on a state-of-the-art language-processing framework that we fit, test, and refine...

This paper provides new evidence on the effects of fiscal policy by studying, using household-level data, how households respond to shifts in government spending. Our identification strategy allows us to control for time-specific aggregate effects, such as the stance of monetary policy or the...

In 1997 Chancellor Kohl proposed a major pension reform and pushed the law through Parliament explaining that the German PAYG system had become unsustainable. One limitation of the new law -- one that is crucial for our identification strategy -- is that it left the generous pension entitlements...