This paper aims to construct a financial health indicator to define the degree of financial health in order to decontaminate the estimation sample and to make predictions that are not biased by unhealthy firms.
The binomial logit model is used to examine the likelihood that a firm will go bankrupt. In order to evaluate the accuracy of the estimated models, measures proposed by the Basel Committee on Banking Supervision are applied: cumulative accuracy profile (CAP) and the receiver operating characteristics (ROC).
The proposed financial health indicator permits the heterogeneity of the firms to be reduced as well as identifying a strong firm sample to estimate the bankruptcy probability accurately.
A drawback of all bankruptcy prediction models comes from the fact that bankruptcy is an example of a homogeneous observable qualitative response while non‐bankruptcy would be expected to be represented by a healthy firm. However, the non‐bankruptcy firms are heterogeneous and their actual probabilities of bankruptcy are non‐observable. The article adds to the previous literature on SMEs' bankruptcy prediction by using a financial health indicator to construct the estimation sample and to make accurate bankruptcy predictions.
