In social sciences and economics, causal inference traditionally focuses on assessing the impact of predefined treatments (or interventions) on predefined outcomes, such as the effect of education programs on earnings. Causal discovery, in contrast, aims to uncover causal relationships among...

We assess the impact of the timing of lockdown measures implemented in Germany and Switzerland on cumulative COVID-19-related hospitalization and death rates. Our analysis exploits the fact that the epidemic was more advanced in some regions than in others when certain lockdown measures came...

In recent years, microeconometrics experienced the "credibility revolution", culminating in the 2021 Nobel prices for David Card, Josh Angrist, and Guido Imbens. This "revolution" in how to do empirical work led to more reliable empirical knowledge of the causal effects of certain public...