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Modelling Bankruptcy Using Hungarian Firm-Level Data

Author

Listed:
  • Péter Bauer

    (Magyar Nemzeti Bank (Central Bank of Hungary))

  • Marianna Endrész

    (Magyar Nemzeti Bank (Central Bank of Hungary))

Abstract

The ultimate aim of this paper is to generate micro-level risk measures, which can provide a useful input for further research. To this end, this paper estimates bankruptcy probabilities for Hungarian firms using probit estimation. The estimated models show reasonable performance in distinguishing surviving and failing firms. We combine macro and micro information, as the addition of macro variables is needed to capture the aggregate dynamics and level of risk, especially during the crisis period. Controlling for the non-linear impact of firm characteristics and allowing heterogeneity by firm size improves the model’s performance significantly. The distributional characteristics of the micro-level risk indicators provide some interesting insights regarding the development of risk dispersion and the risktaking of the banking sector.

Suggested Citation

  • Péter Bauer & Marianna Endrész, 2016. "Modelling Bankruptcy Using Hungarian Firm-Level Data," MNB Occasional Papers 2016/122, Magyar Nemzeti Bank (Central Bank of Hungary).
    • Handle: RePEc:mnb:opaper:2016/122
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    References listed on IDEAS

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    1. Giordani, Paolo & Jacobson, Tor & Schedvin, Erik von & Villani, Mattias, 2014. "Taking the Twists into Account: Predicting Firm Bankruptcy Risk with Splines of Financial Ratios," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(4), pages 1071-1099, August.
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    8. 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.
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    10. Hamerle, Alfred & Liebig, Thilo & Scheule, Harald, 2004. "Forecasting Credit Portfolio Risk," Discussion Paper Series 2: Banking and Financial Studies 2004,01, Deutsche Bundesbank.
    11. Shumway, Tyler, 2001. "Forecasting Bankruptcy More Accurately: A Simple Hazard Model," The Journal of Business, University of Chicago Press, vol. 74(1), pages 101-124, January.
    12. Sreedhar T. Bharath & Tyler Shumway, 2008. "Forecasting Default with the Merton Distance to Default Model," The Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1339-1369, May.
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    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Gergõ Horváth, 2021. "Corporate Credit Risk Modelling in the Supervisory Stress Test of the Magyar Nemzeti Bank," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 20(1), pages 43-73.
    2. Juliana Salomao & Liliana Varela, 2022. "Exchange Rate Exposure and Firm Dynamics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(1), pages 481-514.
    3. Błażej Prusak, 2018. "Review of Research into Enterprise Bankruptcy Prediction in Selected Central and Eastern European Countries," IJFS, MDPI, vol. 6(3), pages 1-28, June.
    4. Tamás Kristóf & Miklós Virág, 2020. "A Comprehensive Review of Corporate Bankruptcy Prediction in Hungary," JRFM, MDPI, vol. 13(2), pages 1-20, February.
    5. György Inzelt & Zsuzsa Szentes-Markhot & Gábor Budai, 2018. "Monitoring of Banks’ Risks Related to the Funding of Financial Enterprises," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 17(4), pages 112-139.
    6. Katarina Valaskova & Dominika Gajdosikova & Jaroslav Belas, 2023. "Bankruptcy prediction in the post-pandemic period: A case study of Visegrad Group countries," Oeconomia Copernicana, Institute of Economic Research, vol. 14(1), pages 253-293, March.
    7. György Inzelt & Gábor Szappanos & Zsolt Armai, 2016. "Supervision by robust risk monitoring – a cycle-independent Hungarian corporate credit rating system," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 15(3), pages 51-78.
    8. Marianna Endrész, 2020. "The bank lending channel during financial turmoil," MNB Working Papers 2020/5, Magyar Nemzeti Bank (Central Bank of Hungary).
    9. Virág, Miklós & Nyitrai, Tamás, 2017. "Magyar vállalkozások felszámolásának előrejelzése pénzügyi mutatóik idősorai alapján [Predicting the liquidation of Hungarian firms using a time series of their financial ratios]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(3), pages 305-324.
    10. Ádám Banai & Szilárd Erhart & Nikolett Vágó & Péter Varga, 2016. "How to set listing criteria for small and medium-sized enterprises in Hungary?," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 15(3), pages 79-109.
    11. Liliana Varela & Juliana Salomao, 2016. "Exchange Rate Exposure and Firm Dynamics," Working Papers 2016-278-05, Department of Economics, University of Houston.

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    More about this item

    Keywords

    bankruptcy risk modelling; probit; micro data;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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