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math.ST2026
Bootstrap consistency for general double/debiased machine learning estimators
Ziming Lin, Fang Han
Double/debiased machine learning (DML) provides a general framework for inference with high-dimensional or otherwise complex nuisance parameters by combining Neyman-orthogonal scor…
math.ST2024
On the consistency of bootstrap for matching estimators
Ziming Lin, Fang Han
In a landmark paper, Abadie and Imbens (2008) showed that the naive bootstrap is inconsistent when applied to nearest neighbor matching estimators of the average treatment effect w…