Motivated by a recent literature on the double-descent phenomenon in mac...
Pre-analysis plans (PAPs) are a potential remedy to the publication of
s...
When we use algorithms to produce recommendations, we typically think of...
We investigate the optimal design of experimental studies that have
pre-...
When machine-learning algorithms are deployed in high-stakes decisions, ...
We characterize optimal oversight of algorithms in a world where an agen...
Instrumental variables (IV) regression is widely used to estimate causal...
The past years have seen seen the development and deployment of
machine-...
Since their introduction in Abadie and Gardeazabal (2003), Synthetic Con...
A core challenge in the analysis of experimental data is that the impact...