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Credit risk and business cycle over different regimes

Author

Listed:
  • Juri Marcucci

    (Bank of Italy, Economic Research Department)

  • Mario Quagliariello

    (Bank of Italy, Banking and Financial Supervision)

Abstract

In the recent banking literature on the relationship between credit risk and the business cycle, the presence of asymmetric effects both across credit risk regimes and through the business cycle has been generally neglected. Employing threshold regression models both at the aggregate and the bank level and exploiting a unique dataset on Italian bank borrowers� default rates, this paper analyzes whether this relationship is characterized by regime switches and thus by asymmetries, determining the thresholds endogenously. Our results show that not only are the effects of the business cycle on credit risk more pronounced during downturns but also when credit risk conditions are poor.

Suggested Citation

  • Juri Marcucci & Mario Quagliariello, 2008. "Credit risk and business cycle over different regimes," Temi di discussione (Economic working papers) 670, Bank of Italy, Economic Research and International Relations Area.
  • Handle: RePEc:bdi:wptemi:td_670_08
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    Citations

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    Cited by:

    1. Grigori Fainstein & Igor Novikov, 2011. "The role of macroeconomic determinants in credit risk measurement in transition country: Estonian example," International Journal of Transitions and Innovation Systems, Inderscience Enterprises Ltd, vol. 1(2), pages 117-137.
    2. Uquillas, Adriana & Tonato, Ronny, 2022. "Inter-portfolio credit risk contagion including macroeconomic and financial factors: A case study for Ecuador," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 299-320.
    3. Grigori Fainstein & Igor Novikov, 2011. "The Comparative Analysis of Credit Risk Determinants In the Banking Sector of the Baltic States," Review of Economics & Finance, Better Advances Press, Canada, vol. 1, pages 20-45, June.
    4. Simona Castellani & Chiara Pederzoli & Costanza Torricelli, 2008. "Indebtedness, macroeconomic conditions and banks’ loan losses: evidence from Italy," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 08014, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    5. Apergis, Nicholas & Eleftheriou, Sofia, 2016. "Gold returns: Do business cycle asymmetries matter? Evidence from an international country sample," Economic Modelling, Elsevier, vol. 57(C), pages 164-170.
    6. Marcucci, Juri & Quagliariello, Mario, 2009. "Asymmetric effects of the business cycle on bank credit risk," Journal of Banking & Finance, Elsevier, vol. 33(9), pages 1624-1635, September.
    7. Mihail Petkovski & Jordan Kjosevski & Kiril Jovanovski, 2018. "Empirical Panel Analysis of Non-performing Loans in the Czech Republic. What are their Determinants and How Strong is their Impact on the Real Economy?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 68(5), pages 460-490, October.
    8. Anastasiou, Dimitrios, 2017. "Is ex-post credit risk affected by the cycles? The case of Italian banks," Research in International Business and Finance, Elsevier, vol. 42(C), pages 242-248.
    9. Dimitrios Anastasiou & Konstantinos Drakos & Stylianos Giannoulakis, 2018. "Are Bank Credit Standards Affected by the Business Cycle? Evidence from the Euro Area," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot GmbH, Berlin, vol. 64(1), pages 5-16.
    10. Anastasiou, Dimitrios, 2017. "The Interplay between Ex-post Credit Risk and the Cycles: Evidence from the Italian banks," MPRA Paper 79470, University Library of Munich, Germany.

    More about this item

    Keywords

    Credit Risk; Panel Threshold Regression Models; Regime Switching; Default Rate; Business Cycle; Cyclicality; Basel 2;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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