IDEAS home Printed from https://ideas.repec.org/a/fru/finjrn/240602p24-41.html
   My bibliography  Save this article

Theoretical and Methodological Approach to Assessing the Probability of Bankruptcy of Enterprises in Economic Sectors

Author

Listed:
  • Ilya V. Naumov

    (Institute of Economics UB RAS, Yekaterinburg, Russian Federation)

  • Anna A. Bychkova

    (Institute of Economics UB RAS, Yekaterinburg, Russian Federation)

  • Natalia L. Nikulina

    (Institute of Economics UB RAS, Yekaterinburg, Russian Federation)

Abstract

In the context of the rapidly changing geopolitical situation and sanctions pressure on the Russian economy, it is critically important to assess the financial stability of enterprises, forecast the risks of decline in their financial solvency and the probability of bankruptcy in order to make effective management decisions on the development of economic sectors in the constituent entities of the Russian Federation. Currently existing methodological approaches to analyzing the probability of enterprise bankruptcy do not allow to fully assess the financial condition of economic sectors in the regions of Russia.The purpose of the work is to identify the advantages and disadvantages of the methods used in practice to analyze the financial solvency of enterprises and their adjustment to forecast the probability of bankruptcy of enterprises in the constituent entities of the Russian Federation. The novelty of the developed methodological approach is the use of multidimensional discriminant analysis of the probability of bankruptcy of enterprises in a specific sector of the economy in a constituent entity of the Russian Federation according to the modified Altman model, which eliminates the factor characterizing the ratio of the market value of shares of all enterprises in the industry to the sum of all liabilities, as well as the calculation of integral values of the probability of bankruptcy of enterprises in the industry with a breakdown into large, medium and small enterprises to study the scale of threats to financial solvency, taking into account industry specifics. In the course of the research the following results were obtained: an original methodological apparatus for assessing the probability of bankruptcy of enterprises in various sectors of the economy was developed, including the calculation of individual threshold values for each sector in the region based on the dynamics observed over a long period of time; zones of probability of bankruptcy of enterprises were determined. The resulting methodology was tested at enterprises of water supply, wastewater disposal, waste collection and utilization and pollution elimination in the Sverdlovsk region. The analysis of their financial condition revealed an increased probability of their bankruptcy. Moreover, the most vulnerable were both the largest and small enterprises which have insufficient liquidity of assets, lack of working capital and developing mainly at the expense of borrowed funds and attracted loans. As a result of the study, not only the insufficient level of financial stability and solvency of water supply, wastewater disposal, waste collection and utilization and pollution control enterprises in the Sverdlovsk region, but also a decreasing in the level of asset turnover and especially accounts receivable, as well as a high level of their debt load, were identified (as the main signs of the threat of bankruptcy). The methodology modified by the authors allows to timely determine the probability of bankruptcy for all enterprises (large, medium, and small) taking into account the industry specifics and to initiate appropriate measures to prevent the critical financial condition of enterprises.

Suggested Citation

  • Ilya V. Naumov & Anna A. Bychkova & Natalia L. Nikulina, 2024. "Theoretical and Methodological Approach to Assessing the Probability of Bankruptcy of Enterprises in Economic Sectors," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 6, pages 24-41, December.
  • Handle: RePEc:fru:finjrn:240602:p:24-41
    DOI: 10.31107/2075-1990-2024-6-24-41
    as

    Download full text from publisher

    File URL: https://www.finjournal-nifi.ru/images/FILES/Journal/Archive/2024/6/statii/02_6_2024_v16.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.31107/2075-1990-2024-6-24-41?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
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    3. Zmijewski, Me, 1984. "Methodological Issues Related To The Estimation Of Financial Distress Prediction Models," Journal of Accounting Research, Wiley Blackwell, vol. 22, pages 59-82.
    4. Altman, Edward I. & Haldeman, Robert G. & Narayanan, P., 1977. "ZETATM analysis A new model to identify bankruptcy risk of corporations," Journal of Banking & Finance, Elsevier, vol. 1(1), pages 29-54, June.
    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. Li, Chunyu & Lou, Chenxin & Luo, Dan & Xing, Kai, 2021. "Chinese corporate distress prediction using LASSO: The role of earnings management," International Review of Financial Analysis, Elsevier, vol. 76(C).
    2. Amin Jan & Maran Marimuthu & Muhammad Kashif Shad & Haseeb ur-Rehman & Muhammad Zahid & Ahmad Ali Jan, 2019. "Bankruptcy profile of the Islamic and conventional banks in Malaysia: a post-crisis period analysis," Economic Change and Restructuring, Springer, vol. 52(1), pages 67-87, February.
    3. du Jardin, Philippe, 2015. "Bankruptcy prediction using terminal failure processes," European Journal of Operational Research, Elsevier, vol. 242(1), pages 286-303.
    4. David A. Hensher & Stewart Jones & William H. Greene, 2007. "An Error Component Logit Analysis of Corporate Bankruptcy and Insolvency Risk in Australia," The Economic Record, The Economic Society of Australia, vol. 83(260), pages 86-103, March.
    5. Grunert, Jens & Norden, Lars & Weber, Martin, 2005. "The role of non-financial factors in internal credit ratings," Journal of Banking & Finance, Elsevier, vol. 29(2), pages 509-531, February.
    6. 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.
    7. Jones, Stewart & Hensher, David A., 2007. "Modelling corporate failure: A multinomial nested logit analysis for unordered outcomes," The British Accounting Review, Elsevier, vol. 39(1), pages 89-107.
    8. Evangelos C. Charalambakis, 2015. "On the Prediction of Corporate Financial Distress in the Light of the Financial Crisis: Empirical Evidence from Greek Listed Firms," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 22(3), pages 407-428, November.
    9. du Jardin, Philippe, 2012. "The influence of variable selection methods on the accuracy of bankruptcy prediction models," MPRA Paper 44383, University Library of Munich, Germany.
    10. Fernando García & Francisco Guijarro & Ismael Moya, 2013. "Monitoring credit risk in the social economy sector by means of a binary goal programming model," Service Business, Springer;Pan-Pacific Business Association, vol. 7(3), pages 483-495, September.
    11. John Nkwoma Inekwe, 2016. "Financial Distress, Employees’ Welfare and Entrepreneurship Among SMEs," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 129(3), pages 1135-1153, December.
    12. Inekwe, John Nkwoma & Jin, Yi & Valenzuela, Ma. Rebecca, 2018. "The effects of financial distress: Evidence from US GDP growth," Economic Modelling, Elsevier, vol. 72(C), pages 8-21.
    13. 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.
    14. Viral Acharya & Sergei A. Davydenko & Ilya A. Strebulaev, 2012. "Cash Holdings and Credit Risk," The Review of Financial Studies, Society for Financial Studies, vol. 25(12), pages 3572-3609.
    15. Sudhir Nanda & Parag Pendharkar, 2001. "Linear models for minimizing misclassification costs in bankruptcy prediction," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 10(3), pages 155-168, September.
    16. Benzion, Uri & Galil, Koresh & Lahav, Eyal & Shapir, Offer Moshe, 2018. "Debt composition and lax screening in the corporate bond market," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 178-189.
    17. Ciampi, Francesco, 2015. "Corporate governance characteristics and default prediction modeling for small enterprises. An empirical analysis of Italian firms," Journal of Business Research, Elsevier, vol. 68(5), pages 1012-1025.
    18. Petr Jakubík & Petr Teplý, 2011. "The JT Index as an Indicator of Financial Stability of Corporate Sector," Prague Economic Papers, Prague University of Economics and Business, vol. 2011(2), pages 157-176.
    19. Qunfeng LIAO & Seyed MEHDIAN, 2016. "Measuring Financial Distress And Predicting Corporate Bankruptcy: An Index Approach," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 17, pages 33-51, June.
    20. Dawen Yan & Guotai Chi & Kin Keung Lai, 2020. "Financial Distress Prediction and Feature Selection in Multiple Periods by Lassoing Unconstrained Distributed Lag Non-linear Models," Mathematics, MDPI, vol. 8(8), pages 1-27, August.

    More about this item

    Keywords

    bankruptcy probability; bankruptcy models; financial stability; economic sectors; multivariate discriminant analysis;
    All these keywords.

    JEL classification:

    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

    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:fru:finjrn:240602:p:24-41. 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: Gennady Ageev (email available below). General contact details of provider: https://edirc.repec.org/data/frigvru.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.