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.
Ng, Marie and Wilcox, Rand R.
"Level Robust Methods Based on the Least Squares Regression Estimator,"
Journal of Modern Applied Statistical Methods:
2, Article 5.
Available at: http://digitalcommons.wayne.edu/jmasm/vol8/iss2/5