Scoring model of the financial health of the electrical engineering industry's non-financial corporations

Abstract

The aim of this paper is to estimate the probability of bankruptcy of the companies from the Slovak electrical engineering industry based on data obtained from financial statements. Parameters of the predictive model were estimated using binary logistic regression. This model is able to predict the probability of a company's bankruptcy based on values of significant explanatory variables (accounts payable turnover ratio (APTR), return on sales (ROS), quick ratio (QR), financial leverage (FL), net working capital/assets (NWC/A)). The model is constructed using the financial data of a large sample of electrical engineering companies from 2017. Resulting estimated odds ratios show that, in the electrical engineering industry, ROS, QR, and NWC/A significantly reduce the likelihood of bankruptcy. In other words, if these financial indicators increase, the probability of bankruptcy decreases. Our results are also applicable to other industries connected with industrial production, especially the mechanical engineering industry.