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How important is the credit channel? An empirical study of the US banking crisis

We examine whether by adding a credit channel to the standard New Keynesian model we can account better for the behaviour of US macroeconomic data up to and including the banking crisis. We use the method of indirect inference which evaluates statistically how far a model's simulated behaviour mimics the behaviour of the data. We find that the model with credit dominates the standard model by a substantial margin. Credit shocks are the main contributor to the variation in the output gap during the crisis.

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Paper provided by Cardiff University, Cardiff Business School, Economics Section in its series Cardiff Economics Working Papers with number E2012/22.

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Length: 32 pages
Date of creation: Aug 2012
Date of revision: Dec 2013
Handle: RePEc:cdf:wpaper:2012/22
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Web page: http://business.cardiff.ac.uk/research/academic-sections/economics/working-papers

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  1. Le, Vo Phuong Mai & Meenagh, David & Minford, Patrick & Wickens, Michael R., 2012. "Testing DSGE models by Indirect inference and other methods: some Monte Carlo experiments," CEPR Discussion Papers 9056, C.E.P.R. Discussion Papers.
  2. Fiorella De Fiore & Oreste Tristani, 2013. "Optimal Monetary Policy in a Model of the Credit Channel," Economic Journal, Royal Economic Society, vol. 123(571), pages 906-931, 09.
  3. Urban Jermann & Vincenzo Quadrini, 2009. "Macroeconomic Effects of Financial Shocks," NBER Working Papers 15338, National Bureau of Economic Research, Inc.
  4. 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.
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  8. Liu, Chunping & Minford, Patrick, 2012. "Comparing behavioural and rational expectations for the US post-war economy," CEPR Discussion Papers 9132, C.E.P.R. Discussion Papers.
  9. Christiano, Lawrence & Rostagno, Massimo & Motto, Roberto, 2010. "Financial factors in economic fluctuations," Working Paper Series 1192, European Central Bank.
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  13. McCallum, Bennett T, 1976. "Rational Expectations and the Natural Rate Hypothesis: Some Consistent Estimates," Econometrica, Econometric Society, vol. 44(1), pages 43-52, January.
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  15. Wickens, Michael R, 1982. "The Efficient Estimation of Econometric Models with Rational Expectations," Review of Economic Studies, Wiley Blackwell, vol. 49(1), pages 55-67, January.
  16. Smith, A A, Jr, 1993. "Estimating Nonlinear Time-Series Models Using Simulated Vector Autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages S63-84, Suppl. De.
  17. Gourieroux, C. & Monfort, A. & Renault, E., 1992. "Indirect Inference," Papers 92.279, Toulouse - GREMAQ.
  18. Minford, Patrick & Ou, Zhirong, 2009. "Testing the Monetary Policy Rule in the US: a Reconsideration of the Fed’s Behaviour," CEPR Discussion Papers 7575, C.E.P.R. Discussion Papers.
  19. Gertler, Mark & Kiyotaki, Nobuhiro, 2010. "Financial Intermediation and Credit Policy in Business Cycle Analysis," Handbook of Monetary Economics, in: Benjamin M. Friedman & Michael Woodford (ed.), Handbook of Monetary Economics, edition 1, volume 3, chapter 11, pages 547-599 Elsevier.
  20. Michel Juillard, 2001. "DYNARE: A program for the simulation of rational expectation models," Computing in Economics and Finance 2001 213, Society for Computational Economics.
  21. Taylor, John B., 1993. "Discretion versus policy rules in practice," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 39(1), pages 195-214, December.
  22. Urban Jermann & Vincenzo Quadrini, 2012. "Erratum: Macroeconomic Effects of Financial Shocks," American Economic Review, American Economic Association, vol. 102(2), pages 1186-1186, April.
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