Lassoing the Determinants of Retirement

DOI10.1080/07474938.2015.1092803zbMath1491.62232OpenAlexW2278382313MaRDI QIDQ5864511

Malene Kallestrup-Lamb, Anders Bredahl Kock, Johannes Tang Kristensen

Publication date: 7 June 2022

Published in: Econometric Reviews (Search for Journal in Brave)

Full work available at URL: https://pure.au.dk/ws/files/121834845/Post_print_Kallestrup_Lamb_2016_Lassoing_the_determinants_of_retirement.pdf

zbMATH Keywords

logistic regressionhigh-dimensional dataoracle propertyLassoadaptive Lassoretirementregister data

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Ridge regression; shrinkage estimators (Lasso) (62J07) Generalized linear models (logistic models) (62J12)

Related Items (2)

Finite-sample results for lasso and stepwise Neyman-orthogonal Poisson estimators ⋮ Model Selection and Shrinkage: An Overview

Uses Software

• glmnet

Cites Work

• Unnamed Item
• The Adaptive Lasso and Its Oracle Properties
• Sparse estimators and the oracle property, or the return of Hodges' estimator
• Statistics for high-dimensional data. Methods, theory and applications.
• Heuristics of instability and stabilization in model selection
• Least squares after model selection in high-dimensional sparse models
• Asymptotic properties of bridge estimators in sparse high-dimensional regression models
• The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Sure Independence Screening for Ultrahigh Dimensional Feature Space
• MODEL SELECTION AND INFERENCE: FACTS AND FICTION

This page was built for publication: Lassoing the Determinants of Retirement