Corporate Failure Prediction of Construction Companies in Poland: Evidence from Logit Model

Abstract

Purpose: This paper aims to develop a corporate failure prediction model for construction companies in Poland that allow assessing their financial situation and credit risk. Design/Methodology/Approach: For this purpose, the following research methods have been used, descriptive and comparative analysis, subject literature review, and logit analysis. The Polish construction companies' financial data in this research come from the Emerging Markets Information Service (EMIS). To achieve the main goal of the research, the logit model was built. The significance test, error matrix, and ROC curve were used to assess the quality of the estimated binary logit model. Findings: Based on the research, we identify seven financial indicators that significantly impact the probability of poor financial condition. The following variables are current assets turnover, debt to assets ratio, operating profit to assets, gross profit to assets, operating profit plus amortization to short-term liabilities, current assets to assets ratio, and equity to assets ratio. The research results show that corporate failure prediction models are interesting and important tools to assess the financial situation. Based on the developed model, it has been found that the growth of debts increases the credit risk of construction companies. Moreover, the increase in the share of current assets in the total assets harms the financial condition. Also, the risk of insolvency decreases with growing profitability measured by the rate of return on assets. Practical Implications: The built logit model can be beneficial for investment loan providers, insurance companies, and entities selecting contractors in construction projects due to the possibility of the credit risk assessment. Originality/Value: The use of logit models to identify statistically significant corporate failure prediction factors for construction companies in Poland.