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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
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    File URL: https://mpra.ub.uni-muenchen.de/114969/1/MPRA_paper_114969.pdf
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    References listed on IDEAS

    as
    1. 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.
    2. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure - Reply," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 123-127.
    3. 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.
    4. 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.
    5. 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.
    6. Wruck, Karen Hopper, 1990. "Financial distress, reorganization, and organizational efficiency," Journal of Financial Economics, Elsevier, vol. 27(2), pages 419-444, October.
    7. repec:bla:jfinan:v:53:y:1998:i:5:p:1443-1493 is not listed on IDEAS
    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)

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    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

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