 Predicting Bankruptcy: Insights from Polish Non-Public Companies (2019–2022)Bernard Kokczynski, Dorota Witkowska and Blazej Socha European Research Studies Journal, 2024, vol. XXVII, issue Special A, 252-264 Abstract: Purpose: This study aims to develop bankruptcy prediction models tailored for Polish non-public companies, using linear discriminant analysis applied to data from 208 companies that filed for bankruptcy between 2019 and 2022. Design/Methodology/Approach: Fisher's linear discrimination is an empirical method of classification. It gives a set of multivariate observations on sets known with certainty to come from two or more populations. The problem is to establish certain rules that assign successive individuals to the correct population of origin with minimal probability of misclassification. We use a survey covered 208 Polish non-public companies that filed for bankruptcy with the court in years 2019 - 2022. These companies (in equal proportions) belong to trade, manufacturing, and service sectors. For each bankrupt, a going concern company with a similar amount of assets was selected. Therefore, the whole set amounted 416 enterprises was created as choice-based and matched sample. Findings: The results demonstrate that models constructed on pandemic dataset are more accurate than pre-pandemic models, with sector-specific models outperforming general ones. Key predictors include the value of assets, financial audits, and management's going-concern assessments. The findings underscore the importance of incorporating both financial and non-financial indicators into bankruptcy prediction and highlight the effectiveness of tailoring models to economic and sectoral conditions. Practical implications: The financial performance of companies has been heavily influenced by the post-COVID-19 economic landscape and geopolitical challenges, including the ongoing Ukrainian conflict. Many businesses have faced disruptions, labor shortages, and inflationary pressures, leading to increased bankruptcy filings, particularly among small and medium-sized enterprises. Originality/Value: This empirical research contributes to advancing predictive tools for corporate financial distress, offering insights for businesses and policymakers to mitigate bankruptcy risks. Keywords: Bankruptcy prediction; financial distress; Polish non-public companies. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ers:journl:v:xxvii:y:2024:i:speciala:p:252-264 Access Statistics for this article More articles in European Research Studies Journal from European Research Studies Journal |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.