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Determinants of corporate exposure at default under distressed economic and financial conditions in a developing economy: the case of Zimbabwe

Author

Listed:
  • Frank Ranganai Matenda

    (University of KwaZulu-Natal)

  • Mabutho Sibanda

    (University of KwaZulu-Natal)

  • Eriyoti Chikodza

    (Great Zimbabwe University)

  • Victor Gumbo

    (University of Botswana)

Abstract

We design ordinary least squares (OLS) regression models to estimate the credit conversion factor (CCF) in order to precisely predict the EAD at the account level for defaulted private nonfinancial corporations having credit lines under distressed economic and financial conditions in a developing economy. Our primary focus is on identifying and interpreting the CCF determinants for the defaulted privately owned corporates with credit lines. We apply the models to a unique real-life cross-sectional dataset of defaulted Zimbabwean private corporations. Our empirical results show that the committed amount, the credit usage, the drawn amount, the time to default, the total assets, the ratio of bank debt to total assets, the current ratio, the earnings before interest and tax to total assets ratio, the real gross domestic product growth rate, and the inflation rate are all substantial drivers of the CCF for Zimbabwean private corporates with credit lines. We observe that accounting information is essential in analysing the CCF for private corporations with credit lines under downturn conditions in a developing country. Furthermore, we reveal that the CCF models' forecasting results and the corresponding EAD estimates are augmented by including macroeconomic variables.

Suggested Citation

  • Frank Ranganai Matenda & Mabutho Sibanda & Eriyoti Chikodza & Victor Gumbo, 2021. "Determinants of corporate exposure at default under distressed economic and financial conditions in a developing economy: the case of Zimbabwe," Risk Management, Palgrave Macmillan, vol. 23(1), pages 123-149, June.
  • Handle: RePEc:pal:risman:v:23:y:2021:i:1:d:10.1057_s41283-021-00071-w
    DOI: 10.1057/s41283-021-00071-w
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    References listed on IDEAS

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    1. Gabriel Jiménez & Jose A. Lopez & Jesus Saurina, 2009. "Empirical Analysis of Corporate Credit Lines," The Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5069-5098, December.
    2. Agarwal, Sumit & Ambrose, Brent W. & Liu, Chunlin, 2006. "Credit Lines and Credit Utilization," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(1), pages 1-22, February.
    3. A Matuszyk & C Mues & L C Thomas, 2010. "Modelling LGD for unsecured personal loans: decision tree approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 393-398, March.
    4. Wang, Hong & Forbes, Catherine S. & Fenech, Jean-Pierre & Vaz, John, 2020. "The determinants of bank loan recovery rates in good times and bad – New evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 177(C), pages 875-897.
    5. Paul Pelzl & María Teresa Valderrama, 2019. "Capital regulations and the management of credit commitments during crisis times," DNB Working Papers 661, Netherlands Central Bank, Research Department.
    6. Evangelos C. Charalambakis & Ian Garrett, 2019. "On corporate financial distress prediction: What can we learn from private firms in a developing economy? Evidence from Greece," Review of Quantitative Finance and Accounting, Springer, vol. 52(2), pages 467-491, February.
    7. Loterman, Gert & Brown, Iain & Martens, David & Mues, Christophe & Baesens, Bart, 2012. "Benchmarking regression algorithms for loss given default modeling," International Journal of Forecasting, Elsevier, vol. 28(1), pages 161-170.
    8. Jose J. Canals-Cerda, 2020. "From Incurred Loss to Current Expected Credit Loss (CECL): A Forensic Analysis of the Allowance for Loan Losses in Unconditionally Cancelable Credit Card Portfolios," Working Papers 20-09, Federal Reserve Bank of Philadelphia.
    9. Peter-Hendrik Ingermann & Frederik Hesse & Christian Bélorgey & Andreas Pfingsten, 2016. "The recovery rate for retail and commercial customers in Germany: a look at collateral and its adjusted market values," Business Research, Springer;German Academic Association for Business Research, vol. 9(2), pages 179-228, August.
    10. Leow, Mindy & Crook, Jonathan, 2016. "A new Mixture model for the estimation of credit card Exposure at Default," European Journal of Operational Research, Elsevier, vol. 249(2), pages 487-497.
    11. repec:srs:journl:jasf:v:2:y:2011:i:1:p:26-46 is not listed on IDEAS
    12. Roni Michaely & Michael R. Roberts, 2012. "Corporate Dividend Policies: Lessons from Private Firms," Review of Financial Studies, Society for Financial Studies, vol. 25(3), pages 711-746.
    13. Ihor Voloshyn, 2017. "Predicting the Utilization Rate and Risk Measures of Committed Credit Facilities," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 240, pages 14-21.
    14. Michael Jacobs, Jr. & Pinaki Bag, 2011. "What Do We Know About Exposure At Default On Contingent Credit Lines A Survey Of The Literature Empirical Analysis And Models," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 2(1), pages 26-46.
    15. Gürtler, Marc & Hibbeln, Martin Thomas & Usselmann, Piet, 2018. "Exposure at default modeling – A theoretical and empirical assessment of estimation approaches and parameter choice," Journal of Banking & Finance, Elsevier, vol. 91(C), pages 176-188.
    16. Tong, Edward N.C. & Mues, Christophe & Brown, Iain & Thomas, Lyn C., 2016. "Exposure at default models with and without the credit conversion factor," European Journal of Operational Research, Elsevier, vol. 252(3), pages 910-920.
    17. Sumit Agarwal & Souphala Chomsisengphet & John C. Driscoll, 2004. "Loan commitments and private firms," Finance and Economics Discussion Series 2004-27, Board of Governors of the Federal Reserve System (U.S.).
    18. Michael Jacobs Jr, 2010. "An Empirical Study of Exposure at Default," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 1(1), pages 31-59.
    19. Jiří Witzany, 2011. "Exposure at Default Modeling with Default Intensities," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2011(4), pages 20-48.
    20. Bandyopadhyay,Arindam, 2016. "Managing Portfolio Credit Risk in Banks," Cambridge Books, Cambridge University Press, number 9781107146471, February.
    21. Amir Sufi, 2009. "Bank Lines of Credit in Corporate Finance: An Empirical Analysis," Review of Financial Studies, Society for Financial Studies, vol. 22(3), pages 1057-1088, March.
    22. Amir Sufi, 2009. "Bank Lines of Credit in Corporate Finance: An Empirical Analysis," Review of Financial Studies, Society for Financial Studies, vol. 22(3), pages 1057-1088.
    23. Gao, Huasheng & Harford, Jarrad & Li, Kai, 2012. "CEO pay cuts and forced turnover: Their causes and consequences," Journal of Corporate Finance, Elsevier, vol. 18(2), pages 291-310.
    24. Willem Daniel Schutte & Tanja Verster & Derek Doody & Helgard Raubenheimer & Peet Jacobus Coetzee & David McMillan, 2020. "A proposed benchmark model using a modularised approach to calculate IFRS 9 expected credit loss," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1735681-173, January.
    25. Shan Luo & Anthony Murphy, 2020. "Understanding the Exposure at Default Risk of Commercial Real Estate Construction and Land Development Loans," Working Papers 2007, Federal Reserve Bank of Dallas.
    26. repec:srs:journl:jasf:v:1:y:2010:i:1:p:31-59 is not listed on IDEAS
    27. Bernd Engelmann & Robert Rauhmeier (ed.), 2011. "The Basel II Risk Parameters," Springer Books, Springer, number 978-3-642-16114-8, November.
    28. Mark S. Carey & Michael B. Gordy, 2007. "The bank as grim reaper: debt composition and recoveries on defaulted debt," Proceedings 1056, Federal Reserve Bank of Chicago.
    29. Bellotti, Tony & Crook, Jonathan, 2012. "Loss given default models incorporating macroeconomic variables for credit cards," International Journal of Forecasting, Elsevier, vol. 28(1), pages 171-182.
    30. Steven N. Kaplan & Luigi Zingales, 1997. "Do Investment-Cash Flow Sensitivities Provide Useful Measures of Financing Constraints?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 112(1), pages 169-215.
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    Cited by:

    1. Frank Ranganai Matenda & Mabutho Sibanda, 2022. "Determinants of Default Probability for Audited and Unaudited SMEs under Stressed Conditions in Zimbabwe," Economies, MDPI, vol. 10(11), pages 1-28, November.
    2. Frank Ranganai Matenda & Mabutho Sibanda & Eriyoti Chikodza & Victor Gumbo, 2022. "Corporate Loan Recovery Rates under Downturn Conditions in a Developing Economy: Evidence from Zimbabwe," Risks, MDPI, vol. 10(10), pages 1-24, October.

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