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Banking crises and nonlinear linkages between credit and output

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  • Dobromił Serwa

Abstract

In this article, we analyse the asymmetric causality linkages between credit growth and output growth during banking crises. We employ a recently developed procedure, based on a bivariate Markov switching model, to test the hypotheses of independence, causality and asymmetric causality between credit and output. Using a sample of 103 banking crises around the world, we find that neither credit nor output takes precedence as a variable in calm and crisis periods, although there is evidence of instantaneous interdependence between the banking and real sector during crises. The results suggest that shocks propagate mostly within a year between the banking sector and the real economy. The linear link between credit growth and output growth is also regime dependent.

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  • Dobromił Serwa, 2012. "Banking crises and nonlinear linkages between credit and output," Applied Economics, Taylor & Francis Journals, vol. 44(8), pages 1025-1040, March.
  • Handle: RePEc:taf:applec:44:y:2012:i:8:p:1025-1040
    DOI: 10.1080/00036846.2010.534064
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    Cited by:

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    2. Stefano Puddu, 2013. "Real Sector and Banking System: Real and Feedback Effects. A Non-Linear VAR Approach," IRENE Working Papers 13-01, IRENE Institute of Economic Research.
    3. Schleer Frauke & Semmler Willi, 2016. "Banking Overleveraging and Macro Instability: A Model and VSTAR Estimations," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 236(6), pages 609-638, December.
    4. Aizenman, Joshua & Noy, Ilan, 2013. "Macroeconomic adjustment and the history of crises in open economies," Journal of International Money and Finance, Elsevier, vol. 38(C), pages 41-58.
    5. Franta, Michal, 2017. "Rare shocks vs. non-linearities: What drives extreme events in the economy? Some empirical evidence," Journal of Economic Dynamics and Control, Elsevier, vol. 75(C), pages 136-157.
    6. Michal Franta, 2016. "The Effect of Nonlinearity between Credit Conditions and Economic Activity on Density Forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(2), pages 147-166, March.

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    More about this item

    JEL classification:

    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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