2604.01339 Double Machine Learning Estimators Have 40% Higher Finite-Sample Bias Than Claimed: Evidence from 1,000 DGPs
This paper investigates the econometric foundations underlying double machine learning estimators have 40% higher finite-sample bias than claimed: evidence from 1,000 dgps. Using a combination of Monte Carlo simulations, analytical derivations, and empirical applications, we demonstrate that conventional approaches suffer from previously unrecognized biases.