Approximate inference in heteroskedastic regressions: A numerical evaluation

DOI10.1080/02664760902803271OpenAlexW1981971260MaRDI QIDQ5123554

Maria da Glória A. Lima, Francisco Cribari-Neto

Publication date: 29 September 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664760902803271

zbMATH Keywords

linear regressionleverage pointheteroskedasticitycovariance matrix estimationquasi-\(t\) test

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items

Testing inference in heteroskedastic linear regressions: a comparison of two alternative approaches ⋮ Testing inference in heteroskedastic fixed effects models ⋮ A new heteroskedasticity-consistent covariance matrix estimator for the linear regression model

Uses Software

• Ox
• AS 256

Cites Work

• Unnamed Item
• A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity
• Asymptotic inference under heteroskedasticity of unknown form
• Econometric and statistical computing using Ox
• Improved heteroscedasticity-consistent covariance matrix estimators
• Heteroskedasticity-consistent covariance matrix estimation:white's estimator and the bootstrap^∗
• Bias-corrected heterosced asticity robust covariance matrix (sandwich) estimators
• Algorithm AS 256: The Distribution of a Quadratic Form in Normal Variables
• Heteroskedasticity-consistent interval estimators
• The Bias of a Heteroskedasticity Consistent Covariance Matrix Estimator
• Estimating Heteroscedastic Variances in Linear Models
• Jackknifing in Unbalanced Situations
• Bootstrap methods for heteroskedastic regression models: evidence on estimation and testing
• Errata: Inference Under Heteroskedasticity and Leveraged Data,Communications in Statistics, Theory and Methods, 36, 1877–1888, 2007
• Computing the distribution of quadratic forms in normal variables