dc.creatorBASSETTO, Camila F.
dc.creatorKALATZIS, Aquiles E. G.
dc.date.accessioned2012-10-19T01:07:32Z
dc.date.accessioned2018-07-04T14:48:05Z
dc.date.available2012-10-19T01:07:32Z
dc.date.available2018-07-04T14:48:05Z
dc.date.created2012-10-19T01:07:32Z
dc.date.issued2011
dc.identifierECONOMIC MODELLING, v.28, n.1/Fev, p.264-271, 2011
dc.identifier0264-9993
dc.identifierhttp://producao.usp.br/handle/BDPI/17833
dc.identifier10.1016/j.econmod.2010.09.003
dc.identifierhttp://dx.doi.org/10.1016/j.econmod.2010.09.003
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1614630
dc.description.abstractThis paper analyses the presence of financial constraint in the investment decisions of 367 Brazilian firms from 1997 to 2004, using a Bayesian econometric model with group-varying parameters. The motivation for this paper is the use of clustering techniques to group firms in a totally endogenous form. In order to classify the firms we used a hybrid clustering method, that is, hierarchical and non-hierarchical clustering techniques jointly. To estimate the parameters a Bayesian approach was considered. Prior distributions were assumed for the parameters, classifying the model in random or fixed effects. Ordinate predictive density criterion was used to select the model providing a better prediction. We tested thirty models and the better prediction considers the presence of 2 groups in the sample, assuming the fixed effect model with a Student t distribution with 20 degrees of freedom for the error. The results indicate robustness in the identification of financial constraint when the firms are classified by the clustering techniques. (C) 2010 Elsevier B.V. All rights reserved.
dc.languageeng
dc.publisherELSEVIER SCIENCE BV
dc.relationEconomic Modelling
dc.rightsCopyright ELSEVIER SCIENCE BV
dc.rightsrestrictedAccess
dc.subjectBayesian econometrics
dc.subjectClustering techniques
dc.subjectFinancial constraint
dc.subjectInvestment decision
dc.titleFinancial distress, financial constraint and investment decision: Evidence from Brazil
dc.typeArtículos de revistas


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