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Social and Behavioral Sciences Commons

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Physical Sciences and Mathematics

Journal of Modern Applied Statistical Methods

Heteroscedasticity

2009

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Level Robust Methods Based On The Least Squares Regression Estimator, Marie Ng, Rand R. Wilcox Nov 2009

Level Robust Methods Based On The Least Squares Regression Estimator, Marie Ng, Rand R. Wilcox

Journal of Modern Applied Statistical Methods

Heteroscedastic consistent covariance matrix (HCCM) estimators provide ways for testing hypotheses about regression coefficients under heteroscedasticity. Recent studies have found that methods combining the HCCM-based test statistic with the wild bootstrap consistently perform better than non-bootstrap HCCM-based methods (Davidson & Flachaire, 2008; Flachaire, 2005; Godfrey, 2006). This finding is more closely examined by considering a broader range of situations which were not included in any of the previous studies. In addition, the latest version of HCCM, HC5 (Cribari-Neto, et al., 2007), is evaluated.