Panel data in accounting and finance: theory and application

Detalhes bibliográficos
Autor(a) principal: Fávero, Luiz Paulo Lopes
Data de Publicação: 2013
Tipo de documento: Artigo
Idioma: eng
por
Título da fonte: BBR. Brazilian Business Review (English edition. Online)
Texto Completo: http://www.bbronline.com.br/index.php/bbr/article/view/236
Resumo: The use of models that involve longitudinal data in accounting and finance is common. However, there is often a lack of proper care regarding the criteria for adopting one model over another as well as an insufficiently detailed discussion of the possible estimators to be studied in each situation. This article presents, in conceptual and applied form, the main panel data estimators that can be used in these areas of knowledge and discusses the definition of the most consistent model to be adopted in function of the data characteristics. The models covered for short panels are the POLS with clustered robust standard errors, with between estimator, fixed effects, fixed effects with clustered robust standard errors, random effects and random effects with clustered robust standard errors. In turn, for long panels, the models discussed are fixed effects, random effects, fixed effects with AR(1) error terms, random effects with AR(1) error terms, POLS with AR(1) errors and pooled FGLS with AR(1) errors. The models are also applied to a real case, based on data from Compustat Global. At the end, the main routines for applying each of the models in Stata are presented.
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spelling Panel data in accounting and finance: theory and applicationDados em painel em contabilidade e finanças: teoria e aplicaçãoPanel dataaccountingfinanceestimation methodsDados em painelcontabilidadefinançasmétodo de estimaçãoThe use of models that involve longitudinal data in accounting and finance is common. However, there is often a lack of proper care regarding the criteria for adopting one model over another as well as an insufficiently detailed discussion of the possible estimators to be studied in each situation. This article presents, in conceptual and applied form, the main panel data estimators that can be used in these areas of knowledge and discusses the definition of the most consistent model to be adopted in function of the data characteristics. The models covered for short panels are the POLS with clustered robust standard errors, with between estimator, fixed effects, fixed effects with clustered robust standard errors, random effects and random effects with clustered robust standard errors. In turn, for long panels, the models discussed are fixed effects, random effects, fixed effects with AR(1) error terms, random effects with AR(1) error terms, POLS with AR(1) errors and pooled FGLS with AR(1) errors. The models are also applied to a real case, based on data from Compustat Global. At the end, the main routines for applying each of the models in Stata are presented.A utilização de modelos que envolvam dados longitudinais em contabilidade e finanças tem sido recorrente. No entanto verifica-se uma falta de cuidado quanto aos critérios para a adoção de um modelo em detrimento de outro, bem como a ausência de uma discussão mais detalhada sobre os possíveis estimadores a serem estudados em cada situação. Este artigo tem por objetivo apresentar, de forma conceitual e aplicada, os principais estimadores de dados em painel que podem ser utilizados nessas áreas do conhecimento, bem como auxiliar na definição do modelo mais consistente a ser adotado, em função das características dos dados. Para um painel curto, são discutidos os modelos POLS com erros-padrão robustos clusterizados, com estimadorbetween, efeitos fixos, efeitos fixos com erros-padrão robustos clusterizados, efeitos aleatórios e efeitos aleatórios com erros-padrão robustos clusterizados. Já para um painel longo, são discutidos os modelos com efeitos fixos, efeitos aleatórios, efeitos fixos com termos de erro AR(1), efeitos aleatórios com termos de erro AR(1), POLS com erros AR(1) e Pooled FGLS com erros AR(1). Este artigo também tem por propósito aplicar tais modelos em um caso real, com base nos dados da Compustat Global. Ao final, são apresentadas as principais rotinas para a aplicação de cada um dos modelos em Stata.FUCAPE Business Shool2013-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPeer-reviewed ArticleArtigo revisado pelos paresapplication/pdfapplication/pdfhttp://www.bbronline.com.br/index.php/bbr/article/view/23610.15728/bbr.2013.10.1.6Brazilian Business Review; Vol. 10 No. 1 (2013): January to March 2013; 127-149Brazilian Business Review; v. 10 n. 1 (2013): Janeiro a Março de 2013; 127-1491808-23861807-734Xreponame:BBR. Brazilian Business Review (English edition. Online)instname:Fucape Business School (FBS)instacron:FBSengporhttp://www.bbronline.com.br/index.php/bbr/article/view/236/357http://www.bbronline.com.br/index.php/bbr/article/view/236/358Fávero, Luiz Paulo Lopesinfo:eu-repo/semantics/openAccess2018-11-06T19:54:02Zoai:ojs.pkp.sfu.ca:article/236Revistahttps://www.bbronline.com.br/index.php/bbr/indexONGhttp://www.bbronline.com.br/index.php/bbr/oai|| bbronline@bbronline.com.br1808-23861808-2386opendoar:2018-11-06T19:54:02BBR. Brazilian Business Review (English edition. Online) - Fucape Business School (FBS)false
dc.title.none.fl_str_mv Panel data in accounting and finance: theory and application
Dados em painel em contabilidade e finanças: teoria e aplicação
title Panel data in accounting and finance: theory and application
spellingShingle Panel data in accounting and finance: theory and application
Fávero, Luiz Paulo Lopes
Panel data
accounting
finance
estimation methods
Dados em painel
contabilidade
finanças
método de estimação
title_short Panel data in accounting and finance: theory and application
title_full Panel data in accounting and finance: theory and application
title_fullStr Panel data in accounting and finance: theory and application
title_full_unstemmed Panel data in accounting and finance: theory and application
title_sort Panel data in accounting and finance: theory and application
author Fávero, Luiz Paulo Lopes
author_facet Fávero, Luiz Paulo Lopes
author_role author
dc.contributor.author.fl_str_mv Fávero, Luiz Paulo Lopes
dc.subject.por.fl_str_mv Panel data
accounting
finance
estimation methods
Dados em painel
contabilidade
finanças
método de estimação
topic Panel data
accounting
finance
estimation methods
Dados em painel
contabilidade
finanças
método de estimação
description The use of models that involve longitudinal data in accounting and finance is common. However, there is often a lack of proper care regarding the criteria for adopting one model over another as well as an insufficiently detailed discussion of the possible estimators to be studied in each situation. This article presents, in conceptual and applied form, the main panel data estimators that can be used in these areas of knowledge and discusses the definition of the most consistent model to be adopted in function of the data characteristics. The models covered for short panels are the POLS with clustered robust standard errors, with between estimator, fixed effects, fixed effects with clustered robust standard errors, random effects and random effects with clustered robust standard errors. In turn, for long panels, the models discussed are fixed effects, random effects, fixed effects with AR(1) error terms, random effects with AR(1) error terms, POLS with AR(1) errors and pooled FGLS with AR(1) errors. The models are also applied to a real case, based on data from Compustat Global. At the end, the main routines for applying each of the models in Stata are presented.
publishDate 2013
dc.date.none.fl_str_mv 2013-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
Artigo revisado pelos pares
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://www.bbronline.com.br/index.php/bbr/article/view/236
10.15728/bbr.2013.10.1.6
url http://www.bbronline.com.br/index.php/bbr/article/view/236
identifier_str_mv 10.15728/bbr.2013.10.1.6
dc.language.iso.fl_str_mv eng
por
language eng
por
dc.relation.none.fl_str_mv http://www.bbronline.com.br/index.php/bbr/article/view/236/357
http://www.bbronline.com.br/index.php/bbr/article/view/236/358
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv FUCAPE Business Shool
publisher.none.fl_str_mv FUCAPE Business Shool
dc.source.none.fl_str_mv Brazilian Business Review; Vol. 10 No. 1 (2013): January to March 2013; 127-149
Brazilian Business Review; v. 10 n. 1 (2013): Janeiro a Março de 2013; 127-149
1808-2386
1807-734X
reponame:BBR. Brazilian Business Review (English edition. Online)
instname:Fucape Business School (FBS)
instacron:FBS
instname_str Fucape Business School (FBS)
instacron_str FBS
institution FBS
reponame_str BBR. Brazilian Business Review (English edition. Online)
collection BBR. Brazilian Business Review (English edition. Online)
repository.name.fl_str_mv BBR. Brazilian Business Review (English edition. Online) - Fucape Business School (FBS)
repository.mail.fl_str_mv || bbronline@bbronline.com.br
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