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Financial distress, financial constraint and investment decision: Evidence from Brazil

机译:财务困境,财务约束和投资决策:来自巴西的证据

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This 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.
机译:本文采用具有组变参数的贝叶斯计量模型,分析了1997年至2004年巴西367家公司投资决策中财务约束的存在。本文的动机是使用聚类技术以完全内生的形式对公司进行分组。为了对公司进行分类,我们使用了混合聚类方法,即联合使用层次和非层次聚类技术。为了估计参数,考虑了贝叶斯方法。假定参数具有先验分布,将模型分为随机效应或固定效应。使用普通预测密度标准来选择提供更好预测的模型。我们测试了30个模型,并且更好的预测考虑了样本中2个组的存在,并假设了固定效应模型的Student t分布具有20个自由度的误差。结果表明,通过聚类技术对企业进行分类时,在识别财务约束方面具有鲁棒性。

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