Double/Debiased CoCoLASSO of Treatment Effects with Mismeasured High-Dimensional Control Variables
含测量误差的高维控制变量下处理效应的双重去偏 CoCoLASSO
We develop an estimator for treatment effects in high-dimensional settings with additive measurement error, a prevalent challenge in modern econometrics. We introduce the Double/Debiased Convex Conditioned LASSO (Double/Debiased CoCoLASSO), which extends the double/debiased machine learning framework to accommodate mismeasured covariates. Our principal contributions are threefold. (1) We construct a Neyman-orthogonal score function that remains valid under measurement error,…