Estimation in the presence of heteroskedasticity of unknown form: a Lasso-based approach

DOI10.1515/jem-2023-0007zbMATH Open1541.62358MaRDI QIDQ6561136

Pierre Perron, Emilio González-Coya

Publication date: 24 June 2024

Published in: Journal of Econometric Methods (Search for Journal in Brave)

zbMATH Keywords

confidence intervalslinear modelmean-squared errornonparametric methodsfeasible generalized least-squares

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)

Cites Work

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• A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity
• The Adaptive Lasso and Its Oracle Properties
• Asymptotic properties of Lasso+mLS and Lasso+Ridge in sparse high-dimensional linear regression
• Resurrecting weighted least squares
• A general approach to Lagrange multiplier model diagnostics
• Relaxed Lasso
• Adapting for heteroscedasticity in linear models
• Hedonic housing prices and the demand for clean air
• Feasible generalized least squares using support vector regression
• Least angle regression. (With discussion)
• Least squares after model selection in high-dimensional sparse models
• On the ``degrees of freedom of the lasso
• Efficient Computation and Model Selection for the Support Vector Regression
• Approximate Power Functions for Some Robust Tests of Regression Coefficients
• Asymptotically Efficient Estimation in the Presence of Heteroskedasticity of Unknown Form
• Efficient estimation of conditional variance functions in stochastic regression
• Nonparametrically Weighted Least Squares Estimation in Heteroscedastic Linear Regression
• Random forests

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