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What causes banking crises? An empirical investigation

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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Paper provided by Cardiff University, Cardiff Business School, Economics Section in its series Cardiff Economics Working Papers with number E2012/14.

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Length: 31 pages
Date of creation: Jun 2012
Date of revision: Apr 2013
Handle: RePEc:cdf:wpaper:2012/14
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  1. Le, Vo Phuong Mai & Meenagh, David & Minford, Patrick & Wickens, Michael, 2011. "How much nominal rigidity is there in the US economy? Testing a new Keynesian DSGE model using indirect inference," Journal of Economic Dynamics and Control, Elsevier, vol. 35(12), pages 2078-2104.
  2. Kimball, Miles S, 1995. "The Quantitative Analytics of the Basic Neomonetarist Model," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 27(4), pages 1241-77, November.
  3. Davidson, James & Meenagh, David & Minford, Patrick & Wickens, Michael, 2010. "Why crises happen - nonstationary macroeconomics," Cardiff Economics Working Papers E2010/13, Cardiff University, Cardiff Business School, Economics Section.
  4. Gourieroux, C. & Monfort, A. & Renault, E., 1992. "Indirect Inference," Papers 92.279, Toulouse - GREMAQ.
  5. Le, Vo Phuong Mai & Minford, Patrick & Wickens, Michael R., 2013. "A Monte Carlo procedure for checking identification in DSGE models," CEPR Discussion Papers 9411, C.E.P.R. Discussion Papers.
  6. Stephan Fahr & Roberto Motto & Massimo Rostagno & Frank Smets & Oreste Tristani, 2013. "A monetary policy strategy in good and bad times: lessons from the recent past," Economic Policy, CEPR;CES;MSH, vol. 28(74), pages 243-288, 04.
  7. Frank Smets & Raf Wouters, 2002. "An estimated dynamic stochastic general equilibrium model of the euro area," Working Paper Research 35, National Bank of Belgium.
  8. Del Negro, Marco & Schorfheide, Frank & Smets, Frank & Wouters, Rafael, 2007. "On the Fit of New Keynesian Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 123-143, April.
  9. Allan W. Gregory & Gregor W. Smith, 1991. "Calibration in Macroeconomics," Working Papers 826, Queen's University, Department of Economics.
  10. Gregory, Allan W & Smith, Gregor W, 1991. "Calibration as Testing: Inference in Simulated Macroeconomic Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(3), pages 297-303, July.
  11. King, Robert G. & Plosser, Charles I. & Rebelo, Sergio T., 1988. "Production, growth and business cycles : I. The basic neoclassical model," Journal of Monetary Economics, Elsevier, vol. 21(2-3), pages 195-232.
  12. Le, Vo Phuong Mai & Meenagh, David & Minford, Patrick & Wickens, Michael, 2012. "Testing DSGE models by Indirect inference and other methods: some Monte Carlo experiments," Cardiff Economics Working Papers E2012/15, Cardiff University, Cardiff Business School, Economics Section.
  13. L. Ingber, 2012. "Adaptive simulated annealing," Lester Ingber Papers 12as, Lester Ingber.
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