IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v14y2021i12p590-d696923.html
   My bibliography  Save this article

A New Approach for Risk of Corporate Bankruptcy Assessment during the COVID-19 Pandemic

Author

Listed:
  • Katarzyna Boratyńska

    (Department of Finance, Institute of Economics and Finance, Warsaw University of Life Sciences—SGGW, Nowoursynowska 166 Street, 02-787 Warsaw, Poland)

Abstract

The consequences of COVID-19 will aggravate existing multidimensional risks and reveal new ones. The research gap allows contributing to recognizing the exogenous risk factors of corporate bankruptcy during the COVID-19 pandemic in EU countries. This study aims at revealing how to evaluate the risk of corporate bankruptcy phenomenon in the COVID-19 times. The question arises as to whether Schumpeter’s creative destruction approach is still accurate. The article concentrates on implementing the fsQCA (fuzzy set Qualitative Comparative Analysis) method to identify and evaluate the main exogenous drivers of corporate bankruptcy in EU countries based on Fragile States Index data. This new approach focuses on fuzzy sets theory. The fsQCA method is a globally recognized alternative to quantitative analysis (in which the causal complexity is ignored) and qualitative methods for examining individual cases (which do not have the tools to generalize on their basis). The research indicates and examines the main external factors that would increase the risk of corporate bankruptcy in EU countries: namely, economic decline, uneven economic development, unemployment rate, demographic pressure, and government debt. The study discusses the influence of zombie companies on economies during the COVID-19 pandemic. Identifying risk factors that determine the threat of corporate bankruptcy may constitute practical recommendations for business and restructuring practitioners, financial institutions, and banking and public sector representatives in creating warning and recovery measures during the COVID-19 pandemic.

Suggested Citation

  • Katarzyna Boratyńska, 2021. "A New Approach for Risk of Corporate Bankruptcy Assessment during the COVID-19 Pandemic," JRFM, MDPI, vol. 14(12), pages 1-14, December.
  • Handle: RePEc:gam:jjrfmx:v:14:y:2021:i:12:p:590-:d:696923
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/14/12/590/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1911-8074/14/12/590/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lukason, Oliver & Laitinen, Erkki K., 2019. "Firm failure processes and components of failure risk: An analysis of European bankrupt firms," Journal of Business Research, Elsevier, vol. 98(C), pages 380-390.
    2. Charles Goodhart & Pojanart Sunirand & Dimitrios Tsomocos, 2006. "A model to analyse financial fragility," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 27(1), pages 107-142, January.
    3. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    4. Ragin, Charles C., 2000. "Fuzzy-Set Social Science," University of Chicago Press Economics Books, University of Chicago Press, edition 1, number 9780226702773, December.
    5. Goodell, John W. & Huynh, Toan Luu Duc, 2020. "Did Congress trade ahead? Considering the reaction of US industries to COVID-19," Finance Research Letters, Elsevier, vol. 36(C).
    6. Ragin, Charles C., 2006. "Set Relations in Social Research: Evaluating Their Consistency and Coverage," Political Analysis, Cambridge University Press, vol. 14(3), pages 291-310, July.
    7. Woodside, Arch G., 2014. "Embrace•perform•model: Complexity theory, contrarian case analysis, and multiple realities," Journal of Business Research, Elsevier, vol. 67(12), pages 2495-2503.
    8. Mazur, Mieszko & Dang, Man & Vega, Miguel, 2021. "COVID-19 and the march 2020 stock market crash. Evidence from S&P1500," Finance Research Letters, Elsevier, vol. 38(C).
    9. Sordi, Serena & Vercelli, Alessandro, 2006. "Financial fragility and economic fluctuations," Journal of Economic Behavior & Organization, Elsevier, vol. 61(4), pages 543-561, December.
    10. Kanno, Masayasu, 2021. "Assessing the impact of COVID-19 on major industries in Japan: A dynamic conditional correlation approach," Research in International Business and Finance, Elsevier, vol. 58(C).
    11. Debanjan Banerjee & Mayank Rai, 2020. "Social isolation in Covid-19: The impact of loneliness," International Journal of Social Psychiatry, , vol. 66(6), pages 525-527, September.
    12. Ben Bernanke & Mark Gertler, 1990. "Financial Fragility and Economic Performance," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 105(1), pages 87-114.
    13. Yasuhiro Sakai, 2016. "J. M. Keynes on probability versus F. H. Knight on uncertainty: reflections on the miracle year of 1921," Evolutionary and Institutional Economics Review, Springer, vol. 13(1), pages 1-21, June.
    14. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    15. Liang, Deron & Lu, Chia-Chi & Tsai, Chih-Fong & Shih, Guan-An, 2016. "Financial ratios and corporate governance indicators in bankruptcy prediction: A comprehensive study," European Journal of Operational Research, Elsevier, vol. 252(2), pages 561-572.
    16. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    17. Boratyńska, Katarzyna & Grzegorzewska, Emilia, 2018. "Bankruptcy prediction in the agribusiness sector: Lessons from quantitative and qualitative approaches," Journal of Business Research, Elsevier, vol. 89(C), pages 175-181.
    18. Stewart Jones, 2017. "Corporate bankruptcy prediction: a high dimensional analysis," Review of Accounting Studies, Springer, vol. 22(3), pages 1366-1422, September.
    19. repec:ucp:bkecon:9780226702766 is not listed on IDEAS
    20. Ashraf, Badar Nadeem, 2020. "Stock markets’ reaction to COVID-19: Cases or fatalities?," Research in International Business and Finance, Elsevier, vol. 54(C).
    Full references (including those not matched with items on IDEAS)

    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. Katarzyna Boratynska, 2021. "Determinants of Economic Fragility in Central and Eastern European Countries FsQCA Approach," European Research Studies Journal, European Research Studies Journal, vol. 0(3B), pages 827-837.
    2. Boratyńska, Katarzyna & Grzegorzewska, Emilia, 2018. "Bankruptcy prediction in the agribusiness sector: Lessons from quantitative and qualitative approaches," Journal of Business Research, Elsevier, vol. 89(C), pages 175-181.
    3. Sami Ben Jabeur & Rabi Belhaj Hassine & Salma Mefteh‐Wali, 2021. "Firm financial performance during the financial crisis: A French case study," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2800-2812, April.
    4. Hakim Lyngstadaas, 2020. "Packages or systems? Working capital management and financial performance among listed U.S. manufacturing firms," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 31(4), pages 403-450, December.
    5. Oliver Lukason & Art Andresson, 2019. "Tax Arrears Versus Financial Ratios in Bankruptcy Prediction," JRFM, MDPI, vol. 12(4), pages 1-13, December.
    6. Keijo Kohv & Oliver Lukason, 2021. "What Best Predicts Corporate Bank Loan Defaults? An Analysis of Three Different Variable Domains," Risks, MDPI, vol. 9(2), pages 1-19, January.
    7. Sami Ben Jabeur & Nicolae Stef & Pedro Carmona, 2023. "Bankruptcy Prediction using the XGBoost Algorithm and Variable Importance Feature Engineering," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 715-741, February.
    8. Alberto Tron & Maurizio Dallocchio & Salvatore Ferri & Federico Colantoni, 2023. "Corporate governance and financial distress: lessons learned from an unconventional approach," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 27(2), pages 425-456, June.
    9. Kanno, Masayasu, 2021. "Assessing the impact of COVID-19 on major industries in Japan: A dynamic conditional correlation approach," Research in International Business and Finance, Elsevier, vol. 58(C).
    10. Oz, Ibrahim Onur & Yelkenci, Tezer & Meral, Gorkem, 2021. "The role of earnings components and machine learning on the revelation of deteriorating firm performance," International Review of Financial Analysis, Elsevier, vol. 77(C).
    11. Jabeur, Sami Ben & Gharib, Cheima & Mefteh-Wali, Salma & Arfi, Wissal Ben, 2021. "CatBoost model and artificial intelligence techniques for corporate failure prediction," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    12. Ashok, Shruti & Corbet, Shaen & Dhingra, Deepika & Goodell, John W. & Kumar, Satish & Yadav, Miklesh Prasad, 2022. "Are energy markets informationally smarter than equity markets? Evidence from the COVID-19 experience," Finance Research Letters, Elsevier, vol. 47(PB).
    13. Haoming Wang & Xiangdong Liu, 2021. "Undersampling bankruptcy prediction: Taiwan bankruptcy data," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-17, July.
    14. Magali Aubert & Geoffroy Enjolras, 2015. "Are short food supply chains a solution for farms facing financial difficulties?," Post-Print hal-02800273, HAL.
    15. Serrano-Cinca, Carlos & Gutiérrez-Nieto, Begoña & Bernate-Valbuena, Martha, 2019. "The use of accounting anomalies indicators to predict business failure," European Management Journal, Elsevier, vol. 37(3), pages 353-375.
    16. Yanfang Zhang & Mushang Lee, 2019. "A Hybrid Model for Addressing the Relationship between Financial Performance and Sustainable Development," Sustainability, MDPI, vol. 11(10), pages 1-15, May.
    17. Casado Yusta, Silvia & Nœ–ez Letamendía, Laura & Pacheco Bonrostro, Joaqu’n Antonio, 2018. "Predicting Corporate Failure: The GRASP-LOGIT Model || Predicci—n de la quiebra empresarial: el modelo GRASP-LOGIT," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 26(1), pages 294-314, Diciembre.
    18. Hyunjung Nam & Won Gyun No & Youngsu Lee, 2017. "Are Commercial Financial Databases Reliable? New Evidence from Korea," Sustainability, MDPI, vol. 9(8), pages 1-23, August.
    19. Ferguson, Graham & Megehee, Carol M. & Woodside, Arch G., 2017. "Culture, religiosity, and economic configural models explaining tipping-behavior prevalence across nations," Tourism Management, Elsevier, vol. 62(C), pages 218-233.
    20. Noora Alzayed & Rasol Eskandari & Hassan Yazdifar, 2023. "Bank failure prediction: corporate governance and financial indicators," Review of Quantitative Finance and Accounting, Springer, vol. 61(2), pages 601-631, August.

    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:jjrfmx:v:14:y:2021:i:12:p:590-:d:696923. 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.