Panel data in accounting and finance: theory and application
AbstractThe 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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Bibliographic InfoArticle provided by Fucape Business School in its journal Brazilian Business Review.
Volume (Year): 10 (2013)
Issue (Month): 1 (January)
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Web page: http://www.bbronline.com.br/
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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Luis David Marques, 2000. "Modelos Dinâmicos com Dados em Painel: Revisão da Literatura," FEP Working Papers 100, Universidade do Porto, Faculdade de Economia do Porto.
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