A class of improved heteroskedasticity-consistent covariance matrix estimators
The heteroskedasticity-consistent covariance matrix estimator proposed by White (1980), also known as HC0, is commonly used in practical applications and is implemented into a number of statistical software. Cribari–Neto, Ferrari & Cordeiro (2000) have developed a bias-adjustment scheme that del...
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2002 |
| País: | Brasil |
| Institución: | Fundação Getulio Vargas (FGV) |
| Repositorio: | Repositório Institucional do FGV (FGV Repositório Digital) |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.fgv.br:10438/12469 |
| Acceso en línea: | http://hdl.handle.net/10438/12469 |
| Access Level: | acceso abierto |
| Palabra clave: | Covariance matrix estimation Heteroskedasticity Linear regression White’s estimator Bias correction Economia Análise de regressão Correlação (Estatística) |
| Sumario: | The heteroskedasticity-consistent covariance matrix estimator proposed by White (1980), also known as HC0, is commonly used in practical applications and is implemented into a number of statistical software. Cribari–Neto, Ferrari & Cordeiro (2000) have developed a bias-adjustment scheme that delivers bias-corrected White estimators. There are several variants of the original White estimator that also commonly used by practitioners. These include the HC1, HC2 and HC3 estimators, which have proven to have superior small-sample behavior relative to White’s estimator. This paper defines a general bias-correction mechamism that can be applied not only to White’s estimator, but to variants of this estimator as well, such as HC1, HC2 and HC3. Numerical evidence on the usefulness of the proposed corrections is also presented. Overall, the results favor the sequence of improved HC2 estimators. |
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