High-dimensional macroeconomic forecasting and variable selection via penalized regression

DOI10.1111/ectj.12117OpenAlexW2862010437WikidataQ129525019 ScholiaQ129525019MaRDI QIDQ5084328

Shinya Tanaka, Yoshimasa Uematsu

Publication date: 24 June 2022

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

Full work available at URL: https://doi.org/10.1111/ectj.12117

zbMATH Keywords

portfolio selectionpenalized regressionmixed data sampling (MIDAS)oracle inequalitymacroeconomic forecastingultra-high-dimensional time series

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (5)

L₀-Regularized Learning for High-Dimensional Additive Hazards Regression ⋮ A Bayesian Framework for Sparse Estimation in High-Dimensional Mixed Frequency Vector Autoregressive Models ⋮ The Bayesian nested Lasso for mixed frequency regression models ⋮ Bayesian MIDAS penalized regressions: estimation, selection, and prediction ⋮ Nonsparse Learning with Latent Variables

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