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

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  • 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
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    References listed on IDEAS

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    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.
    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).
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