Tests for regression models with heteroskedasticity of unknown form

DOI10.1016/j.csda.2005.04.004zbMath1445.62164OpenAlexW2060322593MaRDI QIDQ959357

Leslie G. Godfrey

Publication date: 11 December 2008

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2005.04.004

zbMATH Keywords

bootstrapregressiontestsheteroskedasticity

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05) Nonparametric statistical resampling methods (62G09)

Related Items (12)

Multicolinearity and ridge regression: results on type I errors, power and heteroscedasticity ⋮ Comparing the variances or robust measures of scale of two dependent variables ⋮ Alternative HAC covariance matrix estimators with improved finite sample properties ⋮ Linear regression: robust heteroscedastic confidence bands that have some specified simultaneous probability coverage ⋮ Comparing the variances of two dependent variables ⋮ Bayesian Interpretations of Heteroskedastic Consistent Covariance Estimators Using the Informed Bayesian Bootstrap ⋮ How Reliable are Bootstrap-based Heteroskedasticity Robust Tests? ⋮ Half-life estimation based on the bias-corrected bootstrap: a highest density region approach ⋮ Nonparametric and robust methods. (Editorial) ⋮ Heteroskedasticity-consistent interval estimators ⋮ Comparing Pearson Correlations: Dealing with Heteroscedasticity and Nonnormality ⋮ Heteroscedastic Global Tests that the Regression Parameters for Two or More Independent Groups are Identical

Uses Software

• bootstrap
• bootlib

Cites Work

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• The wild bootstrap, tamed at last
• Simulation-based finite-sample tests for heteroskedasticity and ARCH effects
• A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity
• Asymptotic inference under heteroskedasticity of unknown form
• Bootstrapping heteroskedastic regression models: wild bootstrap vs. pairs bootstrap
• The wild bootstrap and heteroskedasticity-robust tests for serial correlation in dynamic regression models
• Bootstrap procedures under some non-i.i.d. models
• Empirically relevant critical values for hypothesis tests: A bootstrap approach
• An investigation of an unbiased correction for heteroskedasticity and the effects of misspecifying the skedastic function.
• Controlling the finite sample significance levels of heteroskedasticity-robust tests of several linear restrictions on regression coefficients
• Bootstrap and wild bootstrap for high dimensional linear models
• Asymptotic Normality and Consistency of the Least Squares Estimators for Families of Linear Regressions
• A Probability Distribution and Its Uses in Fitting Data
• The robustness, reliabiligy and power of heteroskedasticity tests
• Bootstrap methods for heteroskedastic regression models: evidence on estimation and testing
• A Note on the Efficiency of Sandwich Covariance Matrix Estimation
• Discussion of ‘Data mining reconsidered’

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