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Banking and Currency Crises: Differential Diagnostics for Developed Countries

Author

Listed:
  • Mark Joy
  • Marek Rusnak
  • Katerina Smidkova
  • Borek Vasicek
Abstract
We identify a set of "rules of thumb" that characterise economic, financial and structural conditions preceding the onset of banking and currency crises in 36 advanced economies over 1970–2010. We use the Classification and Regression Tree methodology (CART) and its Random Forest (RF) extension, which permits the detection of key variables driving binary crisis outcomes, allows for interactions among key variables and determines critical tipping points. We distinguish between basic country conditions, country structural characteristics and international developments. We find that crises are more varied than they are similar. For banking crises we find that low net interest rate spreads in the banking sector and a shallow or inverted yield curve are their most important forerunners in the short term, whereas in the longer term it is high house price inflation. For currency crises, high domestic short-term rates coupled with overvalued exchange rates are the most powerful short-term predictors. We find that both country structural characteristics and international developments are relevant banking crisis predictors. Currency crises, however, seem to be driven more by country idiosyncratic, short-term developments. We find that some variables, such as the domestic credit gap, provide important unconditional signals, but it is difficult to use them as conditional signals and, more importantly, to find relevant threshold values.

Suggested Citation

  • Mark Joy & Marek Rusnak & Katerina Smidkova & Borek Vasicek, 2014. "Banking and Currency Crises: Differential Diagnostics for Developed Countries," Working Papers 2014/16, Czech National Bank.
    • Handle: RePEc:cnb:wpaper:2014/16
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    References listed on IDEAS

    as
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    Cited by:

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    2. Levieuge, Grégory & Lucotte, Yannick & Pradines-Jobet, Florian, 2021. "The cost of banking crises: Does the policy framework matter?," Journal of International Money and Finance, Elsevier, vol. 110(C).
    3. Mr. Daniel Leigh & Weicheng Lian & Mr. Marcos Poplawski Ribeiro & Rachel Szymanski & Viktor Tsyrennikov & Hong Yang, 2017. "Exchange Rates and Trade: A Disconnect?," IMF Working Papers 2017/058, International Monetary Fund.
    4. Balaga Mohana Rao & Puja Padhi, 2020. "Common Determinants of the Likelihood of Currency Crises in BRICS," Global Business Review, International Management Institute, vol. 21(3), pages 698-712, June.
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    6. Audit, Dooneshsingh & Alam, Nafis, 2022. "Why have credit variables taken centre stage in predicting systemic banking crises?," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 3(1).
    7. Paola Bongini & Małgorzata Iwanicz-Drozdowska & Paweł Smaga & Bartosz Witkowski, 2018. "In search of a measure of banking sector distress: empirical study of CESEE banking sectors," Risk Management, Palgrave Macmillan, vol. 20(3), pages 242-257, August.
    8. repec:cnb:ocpubv:rb16/1 is not listed on IDEAS
    9. Gunther Tichy, 2020. "Zur Prognostizierbarkeit von Krisen," WIFO Monatsberichte (monthly reports), WIFO, vol. 93(3), pages 193-206, March.
    10. Stéphanie Pamies Sumner & Katia Berti, 2017. "A Complementary Tool to Monitor Fiscal Stress in European Economies," European Economy - Discussion Papers 049, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    11. Bluwstein, Kristina & Buckmann, Marcus & Joseph, Andreas & Kapadia, Sujit & Şimşek, Özgür, 2023. "Credit growth, the yield curve and financial crisis prediction: Evidence from a machine learning approach," Journal of International Economics, Elsevier, vol. 145(C).
    12. Tang, Pan & Tang, Tiantian & Lu, Chennuo, 2024. "Predicting systemic financial risk with interpretable machine learning," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    13. Lanbiao Liu & Chen Chen & Bo Wang, 2022. "Predicting financial crises with machine learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 871-910, August.
    14. du Plessis, Emile, 2022. "Multinomial modeling methods: Predicting four decades of international banking crises," Economic Systems, Elsevier, vol. 46(2).
    15. Marcin Pietrzak, 2021. "Can Financial Soundness Indicators Help Predict Financial Sector Distress?," IMF Working Papers 2021/197, International Monetary Fund.
    16. Iwanicz-Drozdowska Małgorzata & Kurowski Łukasz, 2021. "Keep your friends close and your enemies closer – the case of monetary policy and financial imbalances," German Economic Review, De Gruyter, vol. 22(4), pages 383-414, November.
    17. Bitetto, Alessandro & Cerchiello, Paola & Mertzanis, Charilaos, 2023. "Measuring financial soundness around the world: A machine learning approach," International Review of Financial Analysis, Elsevier, vol. 85(C).
    18. Bjarni G. Einarsson & Kristófer Gunnlaugsson & Thorvardur Tjörvi Ólafsson & Thórarinn G. Pétursson, 2015. "The long history of financial boom-bust cycles in Iceland - Part I: Financial crises," Economics wp68, Department of Economics, Central bank of Iceland.
    19. Tölö, Eero, 2020. "Predicting systemic financial crises with recurrent neural networks," Journal of Financial Stability, Elsevier, vol. 49(C).
    20. Antulov-Fantulin, Nino & Lagravinese, Raffaele & Resce, Giuliano, 2021. "Predicting bankruptcy of local government: A machine learning approach," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 681-699.

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    More about this item

    Keywords

    Banking crises; binary classification tree; currency crises; early warning indicators;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications
    • G01 - Financial Economics - - General - - - Financial Crises

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