Predictor Selection for Doubly Robust Double/debiased Machine Learning Estimators for Causal Inference

Although machine learning (ML) facilitates causal effect estimation in high-dimensional settings, its naive application may introduce regularization and overfitting biases into effect estimates. Double/debiased ML (DML) mitigates these biases through Neyman orthogonality and sample splitting. While