IDEAS home Printed from https://ideas.repec.org/a/vrs/foeste/v20y2020i1p221-231n13.html
   My bibliography  Save this article

An Assessment of the Reliability of Discriminatory Models on the Basis of the Bankruptcy of Comapanies in the Food Industry in Poland

Author

Listed:
  • Kozioł Karolina

    (Uniwersytet Rzeszowski, Kolegium Nauk Społecznych, Instytut Ekonomii i Finansów, M. Ćwiklińskiej 2, 35-601Rzeszów, Poland)

  • Pitera Rafał

    (Uniwersytet Rzeszowski, Kolegium Nauk Społecznych, Instytut Ekonomii i Finansów, M. Ćwiklińskiej 2, 35-601Rzeszów, Poland)

Abstract

Research background: The widespread occurrence of the phenomenon of bankruptcy leads to an analysis of the scale and causes of this phenomenon in Polish conditions. It should be remembered that the features that inextricably accompany the conduct of any business are uncertainty and risk, hence the phenomenon of the bankruptcy of enterprises is not foreign and it is impossible to eliminate.Purpose: Assessment of the credibility of Polish discriminatory models as a method of the early warning of bankruptcy of enterprises on a sample of enterprises from the Polish food industry.Research methodology: Literature review and verification of 10 methods using a linear function of discrimination most frequently adopted by people dealing with bankruptcy issues and examination of the financial condition of companies. The food industry was subject to analysis and financial assessment regarding the forecast of the bankruptcy of companies in the process of empirical verification.Results: The interpretation of the results was based on the financial statements of the survey sample consisting of 50 Polish companies (25 with a good financial condition and 25 that were bankrupt) which in the years 2005–2016 declared bankruptcy).Novelty: The results are based on a sample of food industry companies point to the legitimacy of the research. The use of a linear discriminant function confirms the usefulness of early warning models (prognostic reliability around 70%). The study presents a classification of models according to prognostic reliability. Guided by the criterion of model credibility, one can use tools with high prognostic efficiency in assessing the financial situation.

Suggested Citation

  • Kozioł Karolina & Pitera Rafał, 2020. "An Assessment of the Reliability of Discriminatory Models on the Basis of the Bankruptcy of Comapanies in the Food Industry in Poland," Folia Oeconomica Stetinensia, Sciendo, vol. 20(1), pages 221-231, June.
  • Handle: RePEc:vrs:foeste:v:20:y:2020:i:1:p:221-231:n:13
    DOI: 10.2478/foli-2020-0013
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/foli-2020-0013
    Download Restriction: no

    File URL: https://libkey.io/10.2478/foli-2020-0013?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Keywords

    discriminatory analysis; assessment of reliability; company; bankruptcy forecast; risk;
    All these keywords.

    JEL classification:

    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    Statistics

    Access and download statistics

    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:vrs:foeste:v:20:y:2020:i:1:p:221-231:n:13. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.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.