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What causes banking crises? An empirical investigation

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We add the Bernanke-Gertler-Gilchrist model to a modified version of the Smets-Wouters model of the US in order to explore the causes of the banking crisis. We test the model against the data on HP-detrended data and reestimate it by indirect inference,the resulting model passes the Wald test on output, inflation and interest rates. We then extract the model’s implied residuals on US unfiltered data since 1984 to replicate how the model predicts the crisis. The main banking shock tracks the unfolding ‘sub-prime’ shock, which appears to have been authored mainly by US government intervention. This shock worsens the banking crisis but ‘traditional’ shocks explain the bulk of the crisis,the non-stationarity of the productivity shock plays a key role. Crises occur when there is a ‘run’ of bad shocks,based on this sample they occur on average once every 40 years and when they occur around half are accompanied by financial crisis. Financial shocks on their own, even when extreme, do not cause crises — provided the government acts swiftly to counteract such a shock as happened in this sample.

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  • Le, Vo Phuong Mai & Meenagh, David & Minford, Patrick, 2012. "What causes banking crises? An empirical investigation," Cardiff Economics Working Papers E2012/14, Cardiff University, Cardiff Business School, Economics Section, revised Apr 2013.
  • Handle: RePEc:cdf:wpaper:2012/14
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    Cited by:

    1. Agarwal, Natasha & Milner, Chris & Riaño, Alejandro, 2014. "Credit constraints and spillovers from foreign firms in China," Journal of Banking & Finance, Elsevier, vol. 48(C), pages 261-275.
    2. Vo Le & David Meenagh & Patrick Minford & Zhirong Ou, 2013. "What Causes Banking Crises? An Empirical Investigation for the World Economy," Open Economies Review, Springer, pages 581-611.
    3. Le, Vo Phuong Mai & Meenagh, David & Minford, Patrick, 2016. "Monetarism rides again? US monetary policy in a world of Quantitative Easing," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 44(C), pages 85-102.
    4. Vo Le & Kent Matthews & David Meenagh & Patrick Minford & Zhiguo Xiao, 2014. "Banking and the Macroeconomy in China: A Banking Crisis Deferred?," Open Economies Review, Springer, pages 123-161.
    5. Le, Vo Phuong Mai & Matthews, Kent & Meenagh, David & Minford, Patrick & Xiao, Zhiguo, 2015. "China’s financial crisis – the role of banks and monetary policy," Cardiff Economics Working Papers E2015/1, Cardiff University, Cardiff Business School, Economics Section.
    6. Patrick Minford & Yongdeng Xu & Peng Zhou, 2015. "How Good are Out of Sample Forecasting Tests on DSGE Models?," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), pages 333-351.
    7. Liu, Chunping & Minford, Patrick, 2014. "Comparing behavioural and rational expectations for the US post-war economy," Economic Modelling, Elsevier, vol. 43(C), pages 407-415.
    8. Vo Phuong Mai Le & David Meenagh & Patrick Minford & Michael Wickens & Yongdeng Xu, 2016. "Testing Macro Models by Indirect Inference: A Survey for Users," Open Economies Review, Springer, pages 1-38.
    9. Liu, Chunping & Minford, Patrick, 2014. "How important is the credit channel? An empirical study of the US banking crisis," Journal of Banking & Finance, Elsevier, vol. 41(C), pages 119-134.
    10. Meenagh, David & Minford, Patrick & Wickens, Michael & Xu, Yongdeng, 2016. "What is the truth about DSGE models? Testing by indirect inference," Cardiff Economics Working Papers E2016/14, Cardiff University, Cardiff Business School, Economics Section.
    11. Chevapatrakul, Thanaset & Tee, Kai-Hong, 2014. "The effects of news events on market contagion: Evidence from the 2007–2009 financial crisis," Research in International Business and Finance, Elsevier, pages 83-105.

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    Keywords

    DSGE; Banking; Crisis; Bootstrap;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E1 - Macroeconomics and Monetary Economics - - General Aggregative Models

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