Level robust methods based on the least squares regression estimator

Journal of Modern Applied Statistical Methods

Volumn 8, Issue 2, 2009, Pages 384-395

  Ng, Marie ^a   Wilcox, Rand R ^b  

^a UNIVERSITY OF HONG KONG   (Hong Kong)

^b UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

Bootstrap; Heteroscedasticity; Level robust methods

Indexed keywords

EID: 82355187737     PISSN: 15389472     EISSN: None     Source Type: Journal    
DOI: 10.22237/jmasm/1257033840     Document Type: Article

References (13)

1. Cribari-Neto, F. (2004). Asymptotic inference under heteroscedasticity of unknown form. Computational Statistics & Data Analysis, 45, 215-233.
2. Cribari-Neto, F., Souza, T. C., & Vasconcellos, A. L. P. (2007). Inference under heteroskedasticity and leveraged data. Communication in Statistics -Theory and Methods, 36, 1877-1888.
3. Cribari-Neto, F., Souza, T. C., & Vasconcellos, A. L. P. (2008). Errata: Inference under heteroskedasticity and leveraged data. Communication in Statistics -Theory and Methods, 36, 1877-1888. Communication in Statistics -Theory and Methods, 37, 3329-3330.
4. Davidson, R., & Flachaire, E. (2008). The wild bootstrap, tamed at last. Journal of Econometrics, 146, 162-169.
5. Flachaire, E. (2005). Bootstrapping heteroskedastic regression models: wild bootstrap vs. pairs bootstrap. Computational Statistics & Data Analysis, 49, 361-376.
6. th Ed.). New Jersey: Prentice Hall.
7. Godfrey, L. G. (2006). Tests for regression models with heteroscedasticity of unknown form. Computational Statistics & Data Analysis, 50, 2715-2733.
8. Liu, R. Y. (1988). Bootstrap procedures under some non i.i.d. models. The Annuals of Statistics, 16, 1696-1708.
9. Long, J. S., & Ervin, L. H. (2000). Using heteroscedasticity consistent standard errors in the linear regression model. The American Statistician, 54, 217-224.
10. MacKinnon, J. G., & White, H. (1985). Some heteroscedasticity consistent covariance matrix estimators with improved finite sample properties. Journal of Econometrics, 29, 305-325.
11. Robey, R. R. & Barcikowski, R. S. (1992). Type I error and the number of iterations in Monte Carlo studies of robustness. British Journal of Mathematical and Statistical Psychology, 45, 283-288.
12. Weisberg, S. (1980). Applied Linear Regression. NY: Wiley.
13. White, H. (1980). A heteroskedastic-consistent covariance matrix estimator and a direct test of heteroscedasticity. Econometrica, 48, 817-838.