IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/114969.html
   My bibliography  Save this paper

Эконометрический Анализ Факторов Банкротств Российских Компаний В Обрабатывающем Секторе
[Econometric Analysis of Bankruptcy Factors for Russian Companies in the Manufacturing Industry]

Author

Listed:
  • Bekirova, Olga
  • Zubarev, Andrey

Abstract

This work is devoted to the analysis of the factors influencing the bankruptcy of the Russian manufacturing industry companies for the period from 2012 to 2020. Logistic regression was used as an econometric tool for the modelling the probability of companies’ default. According to the results, financial indicators of profitability, liquidity and business activity play a significant role in explaining the probability of default of Russian manufacturing companies. Special attention was paid to the impact on the probability of bankruptcy of corporate governance and ownership structure factors. First, including these indicators into the model led to an increase in its predictive power. Secondly, CEO-duality increases the stability of the company, and too high maximum share of ownership increases the likelihood of bankruptcy.

Suggested Citation

  • Bekirova, Olga & Zubarev, Andrey, 2022. "Эконометрический Анализ Факторов Банкротств Российских Компаний В Обрабатывающем Секторе [Econometric Analysis of Bankruptcy Factors for Russian Companies in the Manufacturing Industry]," MPRA Paper 114969, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:114969
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/114969/1/MPRA_paper_114969.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Демешев Борис Борисович & Тихонова Анна Сергеевна, 2014. "Прогнозирование Банкротства Российских Компаний: Межотраслевое Сравнение," Higher School of Economics Economic Journal Экономический журнал Высшей школы экономики, CyberLeninka;Федеральное государственное автономное образовательное учреждение высшего образования «Национальный исследовательский университет «Высшая школа экономики», vol. 18(3), pages 359-386.
    2. Guilherme Freitas Cardoso & Fernanda Maciel Peixoto & Flavio Barboza, 2019. "Board structure and financial distress in Brazilian firms," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 15(5), pages 813-828, May.
    3. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure - Reply," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 123-127.
    4. Christian Lohmann & Thorsten Ohliger, 2019. "Using accounting‐based information on young firms to predict bankruptcy," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(8), pages 803-819, December.
    5. Wruck, Karen Hopper, 1990. "Financial distress, reorganization, and organizational efficiency," Journal of Financial Economics, Elsevier, vol. 27(2), pages 419-444, October.
    6. repec:bla:jfinan:v:53:y:1998:i:5:p:1443-1493 is not listed on IDEAS
    7. Natalia Nehrebecka, 2021. "COVID-19: stress-testing non-financial companies: a macroprudential perspective. The experience of Poland," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(2), pages 283-319, June.
    8. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    9. repec:zbw:bofrdp:2004_018 is not listed on IDEAS
    10. Hernandez Tinoco, Mario & Wilson, Nick, 2013. "Financial distress and bankruptcy prediction among listed companies using accounting, market and macroeconomic variables," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 394-419.
    11. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    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. Bekirova, Olga & Zubarev, Andrey, 2022. "Макроэкономические Факторы Банкротства Компаний Обрабатывающей Отрасли В Российской Федерации [Macroeconomic Factors of Corporate Bankruptcy in the Manufacturing Sector in the Russian Federation]," MPRA Paper 114968, University Library of Munich, Germany.
    2. Sumaira Ashraf & Elisabete G. S. Félix & Zélia Serrasqueiro, 2019. "Do Traditional Financial Distress Prediction Models Predict the Early Warning Signs of Financial Distress?," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    3. Zhou, Fanyin & Fu, Lijun & Li, Zhiyong & Xu, Jiawei, 2022. "The recurrence of financial distress: A survival analysis," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1100-1115.
    4. Ahsan Habib & Mabel D' Costa & Hedy Jiaying Huang & Md. Borhan Uddin Bhuiyan & Li Sun, 2020. "Determinants and consequences of financial distress: review of the empirical literature," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(S1), pages 1023-1075, April.
    5. Duc Hong Vo & Binh Ninh Vo Pham & Chi Minh Ho & Michael McAleer, 2019. "Corporate Financial Distress of Industry Level Listings in Vietnam," JRFM, MDPI, vol. 12(4), pages 1-17, September.
    6. Sanjay Sehgal & Ritesh Kumar Mishra & Ajay Jaisawal, 2021. "A search for macroeconomic determinants of corporate financial distress," Indian Economic Review, Springer, vol. 56(2), pages 435-461, December.
    7. Vo, D.H. & Pham, B.V.-N. & Pham, T.V.-T. & McAleer, M.J., 2019. "Corporate Financial Distress of Industry Level Listings in an Emerging Market," Econometric Institute Research Papers EI2019-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Xavier Brédart & Eric Séverin & David Veganzones, 2021. "Human resources and corporate failure prediction modeling: Evidence from Belgium," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1325-1341, November.
    9. David Alaminos & Agustín del Castillo & Manuel Ángel Fernández, 2016. "A Global Model for Bankruptcy Prediction," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-18, November.
    10. Muhammad Shahzad Ijaz & Ahmed Imran Hunjra & Rauf I Azam, 2017. "Forewarning Bankruptcy: An Indigenous Model for Pakistan," Business & Economic Review, Institute of Management Sciences, Peshawar, Pakistan, vol. 9(4), pages 259-286, December.
    11. Ben Jabeur, Sami, 2017. "Bankruptcy prediction using Partial Least Squares Logistic Regression," Journal of Retailing and Consumer Services, Elsevier, vol. 36(C), pages 197-202.
    12. Mário S. Céu & Raquel M. Gaspar, 2023. "Financial Distress in European Vineyards and Olive Groves," Working Papers REM 2023/0266, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    13. Velia Gabriella Cenciarelli & Marco Maria Mattei & Giulio Greco, 2020. "Pressione competitiva e previsione dell?insolvenza," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2020(3), pages 35-58.
    14. Soumya Ranjan Sethi & Dushyant Ashok Mahadik & Rajkiran V. Bilolikar, 2024. "Exploring Trends and Advancements in Financial Distress Prediction Research: A Bibliometric Study," International Journal of Economics and Financial Issues, Econjournals, vol. 14(1), pages 164-179, January.
    15. Elsayed, Mohamed & Elshandidy, Tamer, 2020. "Do narrative-related disclosures predict corporate failure? Evidence from UK non-financial publicly quoted firms," International Review of Financial Analysis, Elsevier, vol. 71(C).
    16. Umair Bin Yousaf & Khalil Jebran & Irfan Ullah, 2024. "Corporate governance and financial distress: A review of the theoretical and empirical literature," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1627-1679, April.
    17. Mohammad Mahdi Mousavi & Jamal Ouenniche, 2018. "Multi-criteria ranking of corporate distress prediction models: empirical evaluation and methodological contributions," Annals of Operations Research, Springer, vol. 271(2), pages 853-886, December.
    18. 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.
    19. Shoukat Ali & Ramiz ur Rehman & Wang Yuan & Muhammad Ishfaq Ahmad & Rizwan Ali, 2022. "Does foreign institutional ownership mediate the nexus between board diversity and the risk of financial distress? A case of an emerging economy of China," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 553-581, September.
    20. Hamid Waqas & Rohani Md-Rus, 2018. "Predicting financial distress: Applicability of O-score model for Pakistani firms," Business and Economic Horizons (BEH), Prague Development Center, vol. 14(2), pages 389-401, April.

    More about this item

    Keywords

    probability of default; logistic regression; corporate governance;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • G34 - Financial Economics - - Corporate Finance and Governance - - - Mergers; Acquisitions; Restructuring; Corporate Governance
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:pra:mprapa:114969. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    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.