DataScience@BI invites Jesper Riis-Vestergaard Sørensen
Assistant Professor Jesper Riis-Vestergaard Sørensen, University of Copenhagen, to present the paper “Selecting Penalty Parameters of High-Dimensional M-Estimators using Bootstrapping after Cross-Validation” (with Denis Chetverikov, UCLA).
- Starts:12:00, 15 October 2024
- Ends:13:00, 15 October 2024
- Location:BI - campus Oslo, B3 inner area - next to meeting room B3i-108 or Zoom
- Contact:Siri Johnsen (siri.johnsen@bi.no)
DataScience@BI invites Assistant Professor Jesper Riis-Vestergaard Sørensen at the University of Copenhagen, Department of Economics will present the paper “Selecting Penalty Parameters of High-Dimensional M-Estimators using Bootstrapping after Cross-Validation” (with Denis Chetverikov, UCLA).
Download paper: https://arxiv.org/abs/2104.04716
Key research areas: Theoretical econometrics and mathematical statistic
Abstract:
“We develop a new method for selecting the penalty parameter for ℓ1-penalized M-estimators in high dimensions, which we refer to as bootstrapping after cross-validation. We derive rates of convergence for the corresponding ℓ1-penalized M-estimator and also for the post-ℓ1-penalized M-estimator, which refits the non-zero parameters of the former estimator without penalty in the criterion function. We demonstrate via simulations that our method is not dominated by cross-validation in terms of estimation errors and outperforms cross-validation in terms of inference. As an illustration, we revisit Fryer Jr (2019), who investigated racial differences in police use of force, and confirm his findings.”