This paper studies how gifts - monetary or in-kind payments - from drug firms to physicians in the US affect prescriptions and drug costs. We estimate heterogeneous treatment effects by combining physician-level data on antidiabetic prescriptions and payments with causal inference and machine...

We propose a new approach to detect and quantify informal employment resulting from irregular migration shocks. Focusing on a largely informal sector, agriculture, and on the exogenous variation from the Arab Spring wave on southern Italian coasts, we use machine-learning techniques to document...

How do men and women differ in their persistence after experiencing failure in a competitive environment? We tackle this question by combining a large online experiment (N=2,086) with machine learning. We find that when losing is unequivocally due to merit, both men and women exhibit a...