Bankruptcy Prediction Models for Construction Companies in the Russian Federation
https://doi.org/10.26794/2587-5671-2019-23-5-62-74
Abstract
The article is concerned with determining the main predictors of bankruptcy in construction organizations in the Russian Federation. Probabilistic prediction of bankruptcy is relevant for both individual companies and sectors of the national economy. Developed a long time ago, the existing bankruptcy prediction methods do not consider the industry specifics of organizations. The article investigates the mechanism for probabilistic prediction of bankruptcy based on logit models. Criteria affecting the bankruptcy probability were substantiated; a mathematical model was proposed to calculate the probability. The provided model was tested in a real company. Based on the sample of small and medium-sized construction companies, the author proposed a logit model reflecting the main factors affecting the financial state of construction companies in Russia and, therefore, the likelihood of their bankruptcy. Testing the model on the actual data from the construction enterprises showed its high predictive power. The study results allow predicting the bankruptcy in construction organizations by means of logit models.
About the Author
A. V. Voiko
Financial University
Russian Federation
Russian Federation
Aleksandr V. Voiko — Cand. Sci. (Econ.), Associate Professor, Department of corporate finance and corporate governance
Moscow
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For citations:
Voiko A.V. Bankruptcy Prediction Models for Construction Companies in the Russian Federation. Finance: Theory and Practice. 2019;23(5):62-74. https://doi.org/10.26794/2587-5671-2019-23-5-62-74
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