Sparse linear models and \(l_1\)-regularized 2SLS with high-dimensional endogenous regressors and instruments

DOI10.1016/j.jeconom.2017.10.002zbMath1394.62096OpenAlexW3123049865MaRDI QIDQ1652952

Ying Zhu

Publication date: 17 July 2018

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jeconom.2017.10.002

zbMATH Keywords

endogeneityhigh-dimensional statisticsLassotwo-stage least squaressparse linear models

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Ridge regression; shrinkage estimators (Lasso) (62J07)

Related Items (5)

Doubly debiased Lasso: high-dimensional inference under hidden confounding ⋮ Breaking the winner's curse in Mendelian randomization: rerandomized inverse variance weighted estimator ⋮ Inference for high-dimensional instrumental variables regression ⋮ -Penalized Pairwise Difference Estimation for a High-Dimensional Censored Regression Model ⋮ Regularization methods for high-dimensional sparse control function models

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