Factors Leading to Default by Russian Manufacturing Companies

Abstract

This study analyzes factors influencing the bankruptcy of companies in the Russian manufacturing industry during the period from 2012 to 2020. Logistic regression was used as an econometric tool for modelling the probability of default by companies. Because there was no standardized database indicating the dates when bankruptcy proceedings for Russian companies commenced, that information had to be obtained independently by the authors from data provided by the SPARK system. Both legal bankruptcy proceedings and the economic reasons for a company’s insolvency, which can be ascertained from financial statements, are treated as a dependent variable. This approach in effect broadens the definition of bankruptcy by permitting a greater number of data points derived from instances in which a company is in financial difficulties but does not go through a legal bankruptcy procedure. The results indicate that financial indicators of profitability, liquidity and business activity play a significant role in explaining the probability of default by Russian manufacturing companies. Two definitions (simple and extended) are applied to corporate governance and ownership structure in order to assess their impact on the probability of bankruptcy. One result is that including these indicators increases the predictive power of the models under either definition. A second outcome is that these indicators have a consistent and significant correlation with the probability of bankruptcy when the causes of economic insolvency are examined. However, that significance is not evident for all sub-sectors of manufacturing in models which apply a simple definition of default. Combining ownership with management tends to increase a company’s stability, but extremely large concentrations of share ownership increase the probability of bankruptcy.