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Global Credit Risk: World, Country and Industry Factors

Author

Listed:
  • Bernd Schwaab

    (European Central Bank, Financial Research, Germany)

  • Siem Jan Koopman

    (VU University Amsterdam, the Netherlands)

  • André Lucas

    (VU University Amsterdam, the Netherlands)

Abstract

This paper investigates the dynamic properties of systematic default risk conditions for firms from different countries, industries, and rating groups. We use a high-dimensional nonlinear non-Gaussian state space model to estimate common components in corporate defaults in a 41 country sample between 1980Q1-2014Q4,covering both the global financial crisis and euro area sovereign debt crises. We find that macro and default-specific world factors are a primary source of default clustering across countries. Defaults cluster more than what is implied by shared exposures to macro factors, indicating that other factors are of high importance as well. For all firms, deviations of systematic default risk from macro fundamentals are correlated with net tightening bank lending standards, implying that bank credit supply and systematic default risk are inversely related.

Suggested Citation

  • Bernd Schwaab & Siem Jan Koopman & André Lucas, 2015. "Global Credit Risk: World, Country and Industry Factors," Tinbergen Institute Discussion Papers 15-029/III/DSF87, Tinbergen Institute.
  • Handle: RePEc:tin:wpaper:20150029
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    Cited by:

    1. Paolo Giudici & Laura Parisi, 2016. "CoRisk: measuring systemic risk through default probability contagion," DEM Working Papers Series 116, University of Pavia, Department of Economics and Management.
    2. Barra, Cristian & Ruggiero, Nazzareno, 2021. "Do microeconomic and macroeconomic factors influence Italian bank credit risk in different local markets? Evidence from cooperative and non-cooperative banks," Journal of Economics and Business, Elsevier, vol. 114(C).
    3. Paolo Giudici & Laura Parisi, 2018. "CoRisk: Credit Risk Contagion with Correlation Network Models," Risks, MDPI, vol. 6(3), pages 1-19, September.
    4. Chamizo, Álvaro & Novales, Alfonso, 2020. "Looking through systemic credit risk: Determinants, stress testing and market value," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 64(C).
    5. Areski Cousin & J'er^ome Lelong & Tom Picard, 2021. "Rating transitions forecasting: a filtering approach," Papers 2109.10567, arXiv.org, revised Jun 2023.
    6. Li, Tangrong & Sun, Xuchu, 2023. "Is controlling shareholders' credit risk contagious to firms? — Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 77(C).
    7. Doemeland,Doerte & Estevão,Marcello & Jooste,Charl & Sampi Bravo,James Robert Ezequiel & Tsiropoulos,Vasileios, 2022. "Debt Vulnerability Analysis : A Multi-Angle Approach," Policy Research Working Paper Series 9929, The World Bank.
    8. Li, Zhong-fei & Zhou, Qi & Chen, Ming & Liu, Qian, 2021. "The impact of COVID-19 on industry-related characteristics and risk contagion," Finance Research Letters, Elsevier, vol. 39(C).
    9. Franch, Fabio & Nocciola, Luca & Vouldis, Angelos, 2024. "Temporal networks and financial contagion," Journal of Financial Stability, Elsevier, vol. 71(C).
    10. Takefumi Yamazaki, 2018. "Financial friction sources in emerging economies: Structural estimation of sovereign default models," Discussion papers ron303, Policy Research Institute, Ministry of Finance Japan.
    11. Areski Cousin & Jérôme Lelong & Tom Picard, 2023. "Rating transitions forecasting: a filtering approach," Post-Print hal-03347521, HAL.
    12. Alfonso Novales & Alvaro Chamizo, 2019. "Splitting Credit Risk into Systemic, Sectorial and Idiosyncratic Components," JRFM, MDPI, vol. 12(3), pages 1-33, August.
    13. Oliver Blümke, 2020. "Estimating the probability of default for no‐default and low‐default portfolios," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(1), pages 89-107, January.
    14. Areski Cousin & Jérôme Lelong & Tom Picard, 2022. "Rating transitions forecasting: a filtering approach," Working Papers hal-03347521, HAL.
    15. Oliver Blümke, 2022. "Multiperiod default probability forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 677-696, July.
    16. Dong, Manh Cuong & Tian, Shaonan & Chen, Cathy W.S., 2018. "Predicting failure risk using financial ratios: Quantile hazard model approach," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 204-220.
    17. Paolo Giudici & Laura Parisi, 2015. "Modeling Systemic Risk with Correlated Stochastic Processes," DEM Working Papers Series 110, University of Pavia, Department of Economics and Management.
    18. Kwon, Tae Yeon & Lee, Yoonjung, 2018. "Industry specific defaults," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 45-58.
    19. Kocsis, Zalan & Monostori, Zoltan, 2016. "The role of country-specific fundamentals in sovereign CDS spreads: Eastern European experiences," Emerging Markets Review, Elsevier, vol. 27(C), pages 140-168.
    20. Paulo V. Carvalho & José D. Curto & Rodrigo Primor, 2022. "Macroeconomic determinants of credit risk: Evidence from the Eurozone," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2054-2072, April.

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    Keywords

    systematic default risk; credit portfolio models; frailty-correlated defaults; international default risk cycles; state space methods;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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