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Modelling the recovery outcomes for defaulted loans: A survival analysis approach

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  • Fenech, Jean Pierre
  • Yap, Ying Kai
  • Shafik, Salwa

Abstract

This study investigates the determinants affecting the recovery outcome for bank loans when firms default. We develop survival analysis models, explaining the transition hazards of bank loan recoveries varying over time within the conditional probability of firms either fully recovering or not. Both loan and recovery covariates are critical for recovery outcomes. Furthermore, we identify a hump-shaped hazard function peaking at 23 months from default date followed by a drop. The log–logistic parametric model describes the best fit. Our results demonstrate the significant covariates affecting loan recovery rates, highlighting the importance for banks to structure their loans in the best possible way.

Suggested Citation

  • Fenech, Jean Pierre & Yap, Ying Kai & Shafik, Salwa, 2016. "Modelling the recovery outcomes for defaulted loans: A survival analysis approach," Economics Letters, Elsevier, vol. 145(C), pages 79-82.
    • Handle: RePEc:eee:ecolet:v:145:y:2016:i:c:p:79-82
    DOI: 10.1016/j.econlet.2016.05.015
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    References listed on IDEAS

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    1. Acharya, Viral V. & Almeida, Heitor & Campello, Murillo, 2007. "Is cash negative debt? A hedging perspective on corporate financial policies," Journal of Financial Intermediation, Elsevier, vol. 16(4), pages 515-554, October.
    2. Khieu, Hinh D. & Mullineaux, Donald J. & Yi, Ha-Chin, 2012. "The determinants of bank loan recovery rates," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 923-933.
    3. Jon Frye, 2000. "Depressing recoveries," Emerging Issues, Federal Reserve Bank of Chicago, issue Oct.
    4. Mario Cleves & William W. Gould & Roberto G. Gutierrez & Yulia Marchenko, 2010. "An Introduction to Survival Analysis Using Stata," Stata Press books, StataCorp LP, edition 3, number saus3, April.
    5. Louis, Philippe & Van Laere, Elisabeth & Baesens, Bart, 2013. "Understanding and predicting bank rating transitions using optimal survival analysis models," Economics Letters, Elsevier, vol. 119(3), pages 280-283.
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    Cited by:

    1. Natalia Nehrebecka, 2019. "Bank loans recovery rate in commercial banks: A case study of non-financial corporations," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 37(1), pages 139-172.
    2. Kacer, Marek & Wilson, Nicholas & Zouari, Sana, 2024. "Defaults on government guaranteed loans by potential high growth firms: Evidence from the COVID-19 period," Economics Letters, Elsevier, vol. 243(C).
    3. Janette Larney & James Samuel Allison & Gerrit Lodewicus Grobler & Marius Smuts, 2023. "Modelling the Time to Write-Off of Non-Performing Loans Using a Promotion Time Cure Model with Parametric Frailty," Mathematics, MDPI, vol. 11(10), pages 1-17, May.
    4. González, Marta Ramos & Ureña, Antonio Partal & Fernández-Aguado, Pilar Gómez, 2018. "Proposal on ELBE and LGD in-default: tackling capital requirements after the financial crisis," Working Paper Series 2165, European Central Bank.
    5. Marta Ramos González & Antonio Partal Ureña & Pilar Gómez Fernández-Aguado, 2021. "Regulatory Estimates for Defaulted Exposures: A Case Study of Spanish Mortgages," Mathematics, MDPI, vol. 9(9), pages 1-9, April.

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