Granada, España
Nowadays, the importance of risk analysis of financial institutions has increased, due to the recent financial and economic crisis. To evaluate this risk, there is a known methodology called CAMELS. The variables of this model are commonly used as explanatory factors in regression model leading to collinearity since these variables may be related between them. In spite of this fact, collinearity is usually disregarded and the model is estimated by ordinary least squares obtaining instable estimations. This paper presents a literature review about the detection and treatment of this problem in the different scientific works that use the variables of CAMELS model as explanatory variables in regression model.
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