IDEAS home Printed from https://ideas.repec.org/p/bca/bocadp/25-10.html

Examining the Links Between Firm Performance and Insolvency

Author

Listed:
  • Dylan Hogg
  • Hossein Jebeli

Abstract

Assessing insolvency dynamics is essential for evaluating the financial health of non-financial corporations and mitigating macroeconomic and financial stability risks. This study leverages a newly created Statistics Canada dataset linking insolvency records with firm-level financial data to develop a robust framework for monitoring insolvency risk. We employ two complementary approaches: a univariate threshold method that establishes critical financial ratio benchmarks and a multivariate econometric model that accounts for interactions among financial indicators. These methods produce debt-at-risk measures that enhance risk assessment by combining simplicity with analytical depth. Finally, we apply these metrics to timely firm-level data, enabling continual monitoring of financial vulnerabilities.

Suggested Citation

  • Dylan Hogg & Hossein Jebeli, 2025. "Examining the Links Between Firm Performance and Insolvency," Discussion Papers 2025-10, Bank of Canada.
    • Handle: RePEc:bca:bocadp:25-10
    DOI: 10.34989/sdp-2025-10
    as

    Download full text from publisher

    File URL: https://doi.org/10.34989/sdp-2025-10
    File Function: Abstract
    Download Restriction: no
    File URL: https://www.bankofcanada.ca/wp-content/uploads/2025/07/sdp2025-10.pdf
    File Function: Full text
    Download Restriction: no
    File URL: https://libkey.io/10.34989/sdp-2025-10?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. Philip Bunn & Victoria Redwood, 2003. "Company accounts based modelling of business failures and the implications for financial stability," Bank of England working papers 210, Bank of England.
    2. Scott, James, 1981. "The probability of bankruptcy: A comparison of empirical predictions and theoretical models," Journal of Banking & Finance, Elsevier, vol. 5(3), pages 317-344, September.
    3. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, John Wiley & Sons, Ltd., 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. Hunter, John & Isachenkova, Natalia, 2006. "Aggregate economy risk and company failure: An examination of UK quoted firms in the early 1990s," Journal of Policy Modeling, Elsevier, vol. 28(8), pages 911-919, November.
    2. Dimitras, A. I. & Slowinski, R. & Susmaga, R. & Zopounidis, C., 1999. "Business failure prediction using rough sets," European Journal of Operational Research, Elsevier, vol. 114(2), pages 263-280, April.
    3. Maurice Peat, 2007. "Factors Affecting the Probability of Bankruptcy: A Managerial Decision Based Approach," Abacus, Accounting Foundation, University of Sydney, vol. 43(3), pages 303-324, September.
    4. Jarmila Horváthová & Martina Mokrišová, 2018. "Risk of Bankruptcy, Its Determinants and Models," Risks, MDPI, vol. 6(4), pages 1-22, October.
    5. 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.
    6. Youssef Zizi & Mohamed Oudgou & Abdeslam El Moudden, 2020. "Determinants and Predictors of SMEs’ Financial Failure: A Logistic Regression Approach," Risks, MDPI, vol. 8(4), pages 1-21, October.
    7. 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.
    8. Hernandez Tinoco, Mario & Holmes, Phil & Wilson, Nick, 2018. "Polytomous response financial distress models: The role of accounting, market and macroeconomic variables," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 276-289.
    9. Balcaen, Sofie & Ooghe, Hubert, 2006. "35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems," The British Accounting Review, Elsevier, vol. 38(1), pages 63-93.
    10. Christian Lohmann & Steffen Möllenhoff & Thorsten Ohliger, 2023. "Nonlinear relationships in bankruptcy prediction and their effect on the profitability of bankruptcy prediction models," Journal of Business Economics, Springer, vol. 93(9), pages 1661-1690, November.
    11. Cakir, Murat, 2005. "Firma Başarısızlığının Dinamiklerinin Belirlenmesinde Makina Öğrenmesi Teknikleri: Ampirik Uygulamalar ve Karşılaştırmalı Analiz [Machine Learning Techniques in Determining the Dynamics of Corporate Financial Distress: An Empirical Treatment and a," MPRA Paper 55975, University Library of Munich, Germany.
    12. Ashraf, Sumaira & Félix, Elisabete G.S. & Serrasqueiro, Zélia, 2020. "Development and testing of an augmented distress prediction model: A comparative study on a developed and an emerging market," Journal of Multinational Financial Management, Elsevier, vol. 57.
    13. Tamás Kristóf & Miklós Virág, 2020. "A Comprehensive Review of Corporate Bankruptcy Prediction in Hungary," JRFM, MDPI, vol. 13(2), pages 1-20, February.
    14. Maurice Peat, 2001. "Bankruptcy Probability: A Theoretical and Empirical Examination," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 20, July-Dece.
    15. Elena Gregova & Katarina Valaskova & Peter Adamko & Milos Tumpach & Jaroslav Jaros, 2020. "Predicting Financial Distress of Slovak Enterprises: Comparison of Selected Traditional and Learning Algorithms Methods," Sustainability, MDPI, vol. 12(10), pages 1-17, May.
    16. García-Gallego, Ana & Mures-Quintana, María-Jesús, 2013. "La muestra de empresas en los modelos de predicción del fracaso: influencia en los resultados de clasificación || The Sample of Firms in Business Failure Prediction Models: Influence on Classification Results," 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. 15(1), pages 133-150, June.
    17. du Jardin, Philippe, 2015. "Bankruptcy prediction using terminal failure processes," European Journal of Operational Research, Elsevier, vol. 242(1), pages 286-303.
    18. Van Laere, Elisabeth & Baesens, Bart, 2010. "The development of a simple and intuitive rating system under Solvency II," Insurance: Mathematics and Economics, Elsevier, vol. 46(3), pages 500-510, June.
    19. M. A. Lagesh & Maram Srikanth & Debashis Acharya, 2018. "Corporate Performance during Business Cycles: Evidence from Indian Manufacturing Firms," Global Business Review, International Management Institute, vol. 19(5), pages 1261-1274, October.
    20. Peresetsky, A. A., 2011. "What factors drive the Russian banks license withdrawal," MPRA Paper 41507, University Library of Munich, Germany.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • L20 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - 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:bca:bocadp:25-10. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/bocgvca.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.