Oracle inequalities, variable selection and uniform inference in high-dimensional correlated random effects panel data models
type: Item
instance of: scholarly article
title: Oracle inequalities, variable selection and uniform inference in high-dimensional correlated random effects panel data models
zbMATH Open document ID: 1443.62208
author: Anders Bredahl Kock
published in: Journal of Econometrics
publication date: 2016-09-13T00:00:00Z
Mathematics Subject Classification ID: 62J07
Mathematics Subject Classification ID: 62J05
Mathematics Subject Classification ID: 62H12
Mathematics Subject Classification ID: 62P20
zbMATH DE Number: 6626833
zbMATH Keywords: panel data
zbMATH Keywords: Lasso
zbMATH Keywords: oracle inequality
zbMATH Keywords: sup-norm bounds
zbMATH Keywords: high-dimensional models
zbMATH Keywords: weak sparsity
zbMATH Keywords: correlated random effects
zbMATH Keywords: Mundlak-Chamberlain
zbMATH Keywords: variable selection
zbMATH Keywords: uniform inference
MaRDI profile type: Publication
OpenAlex ID: W2471863548
cites work: Panel Data Econometrics
cites work: Simultaneous analysis of Lasso and Dantzig selector
cites work: Statistics for high-dimensional data. Methods, theory and applications.
cites work: The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
cites work: Asymptotically honest confidence regions for high dimensional parameters by the desparsified conservative Lasso
cites work: Multivariate regression models for panel data
cites work: Q3709749
cites work: Are Economists More Likely to Hold Stocks?*
cites work: Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
cites work: Sure Independence Screening for Ultrahigh Dimensional Feature Space
cites work: Strong oracle optimality of folded concave penalized estimation
cites work: Tuning Parameter Selection in High Dimensional Penalized Likelihood
cites work: Penalized quantile regression for dynamic panel data
cites work: Invertibility conditions for block matrices and estimates for norms of inverse matrices
cites work: Analysis of Panel Data
cites work: ORACLE EFFICIENT VARIABLE SELECTION IN RANDOM AND FIXED EFFECTS PANEL DATA MODELS
cites work: Quantile regression for longitudinal data
cites work: Robust penalized quantile regression estimation for panel data
cites work: MODEL SELECTION AND INFERENCE: FACTS AND FICTION
cites work: High-dimensional graphs and variable selection with the Lasso
cites work: On the Pooling of Time Series and Cross Section Data
cites work: A unified framework for high-dimensional analysis of \(M\)-estimators with decomposable regularizers
cites work: Panel data methods for fractional response variables with an application to test pass rates
cites work: Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso
cites work: Q4864293
cites work: On asymptotically optimal confidence regions and tests for high-dimensional models
cites work: Q2995585
cites work: Q2995584
cites work: High dimensional inverse covariance matrix estimation via linear programming
cites work: Confidence Intervals for Low Dimensional Parameters in High Dimensional Linear Models
cites work: Q3174050
DOI: 10.1016/J.JECONOM.2016.06.001
description: scientific article; zbMATH DE number 6626833