IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i3p1416-d734994.html
   My bibliography  Save this article

Identifying Symptoms of Bankruptcy Risk Based on Bankruptcy Prediction Models—A Case Study of Poland

Author

Listed:
  • Jerzy Kitowski

    (Institute of Economics and Finance, University of Rzeszów, 35-310 Rzeszow, Poland)

  • Anna Kowal-Pawul

    (Institute of Economics and Finance, University of Rzeszów, 35-310 Rzeszow, Poland)

  • Wojciech Lichota

    (Institute of Economics and Finance, University of Rzeszów, 35-310 Rzeszow, Poland)

Abstract

The article presents selected Polish early warning models (logit and discriminant models) that allow the assessment of the risk of bankruptcy of a company, and the purpose of the considerations is to indicate their prognostic effectiveness in predicting susceptible Polish companies one year before their declarations of bankruptcy. The limitations of these methods were also indicated in unpredictable situations, such as the outbreak of an economic crisis, e.g., caused by a humanitarian crisis—the COVID-19 pandemic. Another aim chosen in the article is a methodological critical assessment of the phenomenon of widespread use of foreign models (including the common Altman method) in the study of the risk of bankruptcy of Polish enterprises. Models developed on a sample of foreign enterprises without prior adaptation to domestic conditions are used all over the world, so the conclusions of the article are applicable internationally. The research was based on a query of Polish and foreign literature in the field of economic and legal aspects of bankruptcy and financial analysis, including, in particular, bankruptcy forecasting. The empirical research analyzes the financial data of 50 Polish enterprises from 2017 to 2018. The effectiveness of the selected bankruptcy forecasting models in identifying enterprises from section C of the Polish economy (industrial processing) that filed for bankruptcy in 2018 and 2019 was tested. The time frame fully allows for the identification and the assessment of the effectiveness of early warning models a year before bankruptcy.

Suggested Citation

  • Jerzy Kitowski & Anna Kowal-Pawul & Wojciech Lichota, 2022. "Identifying Symptoms of Bankruptcy Risk Based on Bankruptcy Prediction Models—A Case Study of Poland," Sustainability, MDPI, vol. 14(3), pages 1-18, January.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:3:p:1416-:d:734994
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/3/1416/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/3/1416/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jarmila Horváthová & Martina Mokrišová, 2018. "Risk of Bankruptcy, Its Determinants and Models," Risks, MDPI, vol. 6(4), pages 1-22, October.
    2. Błażej Prusak, 2018. "Review of Research into Enterprise Bankruptcy Prediction in Selected Central and Eastern European Countries," IJFS, MDPI, vol. 6(3), pages 1-28, June.
    3. Rose-Ackerman, Susan, 1991. "Risk Taking and Ruin: Bankruptcy and Investment Choice," The Journal of Legal Studies, University of Chicago Press, vol. 20(2), pages 277-310, June.
    4. Jonas Mackevičius & Ruta Šneidere & Daiva Tamulevičienė, 2018. "The waves of enterprises bankruptcy and the factors that determine them: the case of Latvia and Lithuania," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 6(1), pages 100-114, September.
    5. Jonas Mackevičius & Ruta Šneidere & Daiva Tamulevičienė, 2018. "The waves of enterprises bankruptcy and the factors that determine them: the case of Latvia and Lithuania," Post-Print hal-02121037, HAL.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Katarina Valaskova & Dominika Gajdosikova & Jaroslav Belas, 2023. "Bankruptcy prediction in the post-pandemic period: A case study of Visegrad Group countries," Oeconomia Copernicana, Institute of Economic Research, vol. 14(1), pages 253-293, March.
    2. Beata Gavurova & Sylvia Jencova & Radovan Bacik & Marta Miskufova & Stanislav Letkovsky, 2022. "Artificial intelligence in predicting the bankruptcy of non-financial corporations," Oeconomia Copernicana, Institute of Economic Research, vol. 13(4), pages 1215-1251, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mangirdas Morkunas & Gintaras Cernius & Gintare Giriuniene, 2019. "Assessing Business Risks of Natural Gas Trading Companies: Evidence from GET Baltic," Energies, MDPI, vol. 12(14), pages 1-14, July.
    2. Theodore Metaxas & Athanasios Romanopoulos, 2023. "A Literature Review on the Financial Determinants of Hotel Default," JRFM, MDPI, vol. 16(7), pages 1-19, July.
    3. Katarina Valaskova & Pavol Durana & Peter Adamko & Jaroslav Jaros, 2020. "Financial Compass for Slovak Enterprises: Modeling Economic Stability of Agricultural Entities," JRFM, MDPI, vol. 13(5), pages 1-16, May.
    4. Dorohan-Pysarenko, Liudmyla & Rębilas, Rafał & Yehorova, Olena & Yasnolob, Ilona & Kononenko, Zhanna, 2021. "Methodological peculiarities of probability estimation of bankruptcy of agrarian enterprises in Ukraine," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 7(2), June.
    5. Minhas Akbar & Ahsan Akbar & Petra Maresova & Minghui Yang & Hafiz Muhammad Arshad, 2020. "Unraveling the Bankruptcy Risk‒Return Paradox across the Corporate Life Cycle," Sustainability, MDPI, vol. 12(9), pages 1-19, April.
    6. Le, Son & Sukhatme, Neel U., 2020. "Reaching for mediocrity: Competition and stagnation in pharmaceutical innovation," International Review of Law and Economics, Elsevier, vol. 64(C).
    7. repec:thr:techub:10025:y:2021:i:1:p:567-582 is not listed on IDEAS
    8. Muhammad Ramadhani Kesuma & Felisitas Defung & Anisa Kusumawardani, 2021. "Bankruptcy Prediction And Its Effect On Stock Prices As Impact Of The COVID-19 Pandemic," Technium Social Sciences Journal, Technium Science, vol. 25(1), pages 567-582, November.
    9. Vavrek, Roman & Vozárová, Ivana Kravčáková & Kotulič, Rastislav & Adamišin, Peter & Dubravská, Mariana & Ivanková, Viera, 2022. "Assessing the financial health of agricultural enterprises incorporating the spatial dimension," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 25(3), March.
    10. Elena Gregova & Katarina Valaskova & Peter Adamko & Milos Tumpach & Jaroslav Jaros, 2020. "Predicting Financial Distress of Slovak Enterprises: Comparison of Selected Traditional and Learning Algorithms Methods," Sustainability, MDPI, vol. 12(10), pages 1-17, May.
    11. Michal Pavlicko & Jaroslav Mazanec, 2022. "Minimalistic Logit Model as an Effective Tool for Predicting the Risk of Financial Distress in the Visegrad Group," Mathematics, MDPI, vol. 10(8), pages 1-22, April.
    12. Tarbalouti, Mr, 2010. "Défaut de paiement,Achat de consentement et efficience économique [Default, purchase of consent and economic effeciency]," MPRA Paper 56220, University Library of Munich, Germany.
    13. Chad Syverson, 2011. "What Determines Productivity?," Journal of Economic Literature, American Economic Association, vol. 49(2), pages 326-365, June.
    14. Dagmar Camska & Jiri Klecka, 2020. "Comparison of Prediction Models Applied in Economic Recession and Expansion," JRFM, MDPI, vol. 13(3), pages 1-16, March.
    15. Gianfranco Lombardo & Mattia Pellegrino & George Adosoglou & Stefano Cagnoni & Panos M. Pardalos & Agostino Poggi, 2022. "Machine Learning for Bankruptcy Prediction in the American Stock Market: Dataset and Benchmarks," Future Internet, MDPI, vol. 14(8), pages 1-23, August.
    16. Tarbalouti, Essaid, 2010. "Les déterminants théoriques de la faillite de l’entrepreneur et l’efficience de l’allocation du risque juridique : un survol de littérature [Theoretical determinants of the bankruptcy of the entrep," MPRA Paper 56257, University Library of Munich, Germany.
    17. Oded Stark, 2019. "On Social Preferences and the Intensity of Risk Aversion," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 86(3), pages 807-826, September.
    18. Joanna Wieprow & Agnieszka Gawlik, 2021. "The Use of Discriminant Analysis to Assess the Risk of Bankruptcy of Enterprises in Crisis Conditions Using the Example of the Tourism Sector in Poland," Risks, MDPI, vol. 9(4), pages 1-11, April.
    19. Błażej Prusak & Paweł Galiński, 2021. "Approval of an Arrangement in the Restructuring Proceedings and the Financial Condition of Companies Listed on the Stock Exchanges in Warsaw. Is There Any Relationship?," JRFM, MDPI, vol. 14(11), pages 1-16, November.
    20. Omer Bagais & Khaled Aljaaidi & Abdulaziz Alothman, 2021. "An Empirical Investigation of the Associations of Short and Long Debt Policies with Economic Values of Energy Sector," International Journal of Energy Economics and Policy, Econjournals, vol. 11(1), pages 249-254.
    21. Tyshchenko, Viktoriia & Achkasova, Svitlana & Karpova, Vlada & Kanyhin, Sergii, 2023. "Assesment the influence of debt capital on the bankruptcy of enterprises in the agricultural sector," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 9(2), June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:3:p:1416-:d:734994. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.