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Why is credit-to-GDP a good measure for setting countercyclical capital buffers?

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  • Jokivuolle, Esa
  • Pesola, Jarmo
  • Viren, Matti

Abstract

We examine banks’ loan losses in Europe in 1982–2012 using a nonlinear three-factor model that takes into account output growth, real interest rate, and the ratio of private credit to GDP relative to its trend (i.e., “excessive indebtedness”). We find that a drop in output has an intensified impact on loan losses if the private sector is excessively indebted. Because increased bank credit risk should be matched with higher bank capital, the result motivates the Basel III's countercyclical capital buffers as a function of private indebtedness relative to its trend. The result also helps to explain differences in the amount of loan losses in different recessions across time and across countries. The model also indicates that low interest rates during the recent recession have clearly mitigated loan losses.

Suggested Citation

  • Jokivuolle, Esa & Pesola, Jarmo & Viren, Matti, 2015. "Why is credit-to-GDP a good measure for setting countercyclical capital buffers?," Journal of Financial Stability, Elsevier, vol. 18(C), pages 117-126.
  • Handle: RePEc:eee:finsta:v:18:y:2015:i:c:p:117-126
    DOI: 10.1016/j.jfs.2015.03.005
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    10. Widiantoro, Dimas Mukhlas, 2022. "Countercyclical capital buffer: building the resilience or taming the rapid financial cycle?," MPRA Paper 113507, University Library of Munich, Germany.
    11. Ristolainen, Kim, 2018. "Getting better? The effect of the single supervisory mechanism on banks' loan loss reporting and loan loss reserves," Research Discussion Papers 11/2018, Bank of Finland.
    12. Virtanen, Timo & Tölö, Eero & Virén, Matti & Taipalus, Katja, 2016. "Use of unit root methods in early warning of financial crises," Bank of Finland Research Discussion Papers 27/2016, Bank of Finland.
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    18. Ristolainen, Kim, 2018. "Getting better? The effect of the single supervisory mechanism on banks' loan loss reporting and loan loss reserves," Bank of Finland Research Discussion Papers 11/2018, Bank of Finland.
    19. Ghosh, Amit, 2015. "Banking-industry specific and regional economic determinants of non-performing loans: Evidence from US states," Journal of Financial Stability, Elsevier, vol. 20(C), pages 93-104.
    20. Virtanen, Timo & Tölö, Eero & Virén, Matti & Taipalus, Katja, 2018. "Can bubble theory foresee banking crises?," Journal of Financial Stability, Elsevier, vol. 36(C), pages 66-81.
    21. de Moraes, Claudio Oliveira & Costa, Ágata, 2023. "Credit behavior and financial stability in an emerging economy," Economic Systems, Elsevier, vol. 47(2).
    22. Deli, Yota D. & Hasan, Iftekhar, 2017. "Real effects of bank capital regulations: Global evidence," Journal of Banking & Finance, Elsevier, vol. 82(C), pages 217-228.
    23. Kuttner, Kenneth N. & Shim, Ilhyock, 2016. "Can non-interest rate policies stabilize housing markets? Evidence from a panel of 57 economies," Journal of Financial Stability, Elsevier, vol. 26(C), pages 31-44.
    24. Wang, Xiaoting & Hou, Siyuan & Shen, Jie, 2021. "Default clustering of the nonfinancial sector and systemic risk: Evidence from China," Economic Modelling, Elsevier, vol. 96(C), pages 196-208.
    25. Jun Gao & Ning Xu & Ju Zhou, 2023. "Innovative City Construction and Urban Environmental Performance: Empirical Evidence from China," Sustainability, MDPI, vol. 15(12), pages 1-22, June.

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    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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