A class of improved heteroskedasticity-consistent covariance matrix estimators
Autor(a) principal: | |
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Data de Publicação: | 2002 |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional do FGV (FGV Repositório Digital) |
Texto Completo: | http://hdl.handle.net/10438/12469 |
Resumo: | 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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Cribari Neto, FranciscoEscolas::EPGEFGV2014-11-18T12:17:18Z2014-11-18T12:17:18Z2002-09-05http://hdl.handle.net/10438/12469The 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.engEscola de Pós-Graduação em Economia da FGVSeminários de pesquisa econômica da EPGETodo cuidado foi dispensado para respeitar os direitos autorais deste trabalho. Entretanto, caso esta obra aqui depositada seja protegida por direitos autorais externos a esta instituição, contamos com a compreensão do autor e solicitamos que o mesmo faça contato através do Fale Conosco para que possamos tomar as providências cabíveisinfo:eu-repo/semantics/openAccessCovariance matrix estimationHeteroskedasticityLinear regressionWhite’s estimatorBias correctionEconomiaAnálise de regressãoCorrelação (Estatística)A class of improved heteroskedasticity-consistent covariance matrix estimatorsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlereponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVORIGINAL1103.pdf1103.pdfapplication/pdf248358https://repositorio.fgv.br/bitstreams/d73a4edd-8eb8-48e3-b2fe-72cd610cecb4/downloadacc24c8258c851dfbc3563b89ed31d82MD51LICENSElicense.txtlicense.txttext/plain; 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dc.title.eng.fl_str_mv |
A class of improved heteroskedasticity-consistent covariance matrix estimators |
title |
A class of improved heteroskedasticity-consistent covariance matrix estimators |
spellingShingle |
A class of improved heteroskedasticity-consistent covariance matrix estimators Cribari Neto, Francisco Covariance matrix estimation Heteroskedasticity Linear regression White’s estimator Bias correction Economia Análise de regressão Correlação (Estatística) |
title_short |
A class of improved heteroskedasticity-consistent covariance matrix estimators |
title_full |
A class of improved heteroskedasticity-consistent covariance matrix estimators |
title_fullStr |
A class of improved heteroskedasticity-consistent covariance matrix estimators |
title_full_unstemmed |
A class of improved heteroskedasticity-consistent covariance matrix estimators |
title_sort |
A class of improved heteroskedasticity-consistent covariance matrix estimators |
author |
Cribari Neto, Francisco |
author_facet |
Cribari Neto, Francisco |
author_role |
author |
dc.contributor.unidadefgv.por.fl_str_mv |
Escolas::EPGE |
dc.contributor.affiliation.none.fl_str_mv |
FGV |
dc.contributor.author.fl_str_mv |
Cribari Neto, Francisco |
dc.subject.eng.fl_str_mv |
Covariance matrix estimation Heteroskedasticity Linear regression White’s estimator Bias correction |
topic |
Covariance matrix estimation Heteroskedasticity Linear regression White’s estimator Bias correction Economia Análise de regressão Correlação (Estatística) |
dc.subject.area.por.fl_str_mv |
Economia |
dc.subject.bibliodata.por.fl_str_mv |
Análise de regressão Correlação (Estatística) |
description |
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. |
publishDate |
2002 |
dc.date.issued.fl_str_mv |
2002-09-05 |
dc.date.accessioned.fl_str_mv |
2014-11-18T12:17:18Z |
dc.date.available.fl_str_mv |
2014-11-18T12:17:18Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10438/12469 |
url |
http://hdl.handle.net/10438/12469 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartofseries.por.fl_str_mv |
Seminários de pesquisa econômica da EPGE |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Escola de Pós-Graduação em Economia da FGV |
publisher.none.fl_str_mv |
Escola de Pós-Graduação em Economia da FGV |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional do FGV (FGV Repositório Digital) instname:Fundação Getulio Vargas (FGV) instacron:FGV |
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Fundação Getulio Vargas (FGV) |
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FGV |
institution |
FGV |
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Repositório Institucional do FGV (FGV Repositório Digital) |
collection |
Repositório Institucional do FGV (FGV Repositório Digital) |
bitstream.url.fl_str_mv |
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