Selecting Penalty Parameters of High-Dimensional M-Estimators Using Bootstrapping after Cross Validation.

We develop a new method for selecting the penalty parameter for ℓ-penalized M-estimators in high dimensions, which we refer to as bootstrapping after cross validation. We derive rates of convergence for the corresponding ℓ-penalized M-estimator and also for the post-ℓ-penalized M-estimator, which re...

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Bibliographic Details

Published in:	Journal of Political Economy Vol. 133; no. 10; pp. 3208 - 3249
Main Authors:	Chetverikov, Denis, Sørensen, Jesper Riis-Vestergaard
Format:	Article
Published:	University of Chicago Press Oct2025
Subjects:	Racial differences Statistical bootstrapping Regularization parameter Model validation Simulation methods & models Sampling errors Asymptotic analysis
Online Access:	View this record in EBSCOhost