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Shocks and Frictions in US Business Cycles : a Bayesian DSGE Approach

  • Frank Smets

    ()

    (ECB, CEPR and University of Ghent)

  • Raf Wouters

    ()

    (National Bank of Belgium, Research Department)

Using a Bayesian likelihood approach, we estimate a dynamic stochastic general equilibrium model for the US economy using seven macro-economic time series. The model incorporates many types of real and nominal frictions and seven types of structural shocks. We show that this model is able to compete with Bayesian Vector Autoregression models in out-of-sample prediction. We investigate the relative empirical importance of the various frictions. Finally, using the estimated model we address a number of key issues in business cycle analysis: What are the sources of business cycle fluctuations? Can the model explain the cross-correlation between output and inflation? What are the effects of productivity on hours worked? What are the sources of the “Great Moderation”?

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File URL: https://www.nbb.be/doc/oc/repec/reswpp/wp109en.pdf
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Paper provided by National Bank of Belgium in its series Working Paper Research with number 109.

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Length: 58 pages
Date of creation: Feb 2007
Date of revision:
Handle: RePEc:nbb:reswpp:200702-05
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  1. Robert G. King & Sergio T. Rebelo, 2000. "Resuscitating Real Business Cycles," NBER Working Papers 7534, National Bureau of Economic Research, Inc.
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  4. Chang, Yongsung & Gomes, Joao F & Schorfheide, Frank, 2002. "Learning by Doing as a Propagation Mechanism," CEPR Discussion Papers 3599, C.E.P.R. Discussion Papers.
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  14. Bauwens, Luc & Lubrano, Michel & Richard, Jean-Francois, 2000. "Bayesian Inference in Dynamic Econometric Models," OUP Catalogue, Oxford University Press, number 9780198773139, July.
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  18. Julio Rotemberg & Michael Woodford, 1997. "An Optimization-Based Econometric Framework for the Evaluation of Monetary Policy," NBER Chapters, in: NBER Macroeconomics Annual 1997, Volume 12, pages 297-361 National Bureau of Economic Research, Inc.
  19. Christopher A. Sims & Tao Zha, 2006. "Were There Regime Switches in U.S. Monetary Policy?," American Economic Review, American Economic Association, vol. 96(1), pages 54-81, March.
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  22. Dedola, Luca & Neri, Stefano, 2006. "What does a technology shock do? A VAR analysis with model-based sign restrictions," Working Paper Series 0705, European Central Bank.
  23. Miles S. Kimball, 1995. "The Quantitative Analytics of the Basic Neomonetarist Model," NBER Working Papers 5046, National Bureau of Economic Research, Inc.
  24. 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.
  25. John Geweke, 1999. "Using simulation methods for bayesian econometric models: inference, development,and communication," Econometric Reviews, Taylor & Francis Journals, vol. 18(1), pages 1-73.
  26. Mark Bils & Peter J. Klenow, 2004. "Some Evidence on the Importance of Sticky Prices," Journal of Political Economy, University of Chicago Press, vol. 112(5), pages 947-985, October.
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  28. Galí, Jordi & Rabanal, Pau, 2004. "Technology Shocks and Aggregate Fluctuations: How Well Does the RBC Model Fit Post-War US Data?," CEPR Discussion Papers 4522, C.E.P.R. Discussion Papers.
  29. Neville Francis & Valerie A. Ramey, 2002. "Is the Technology-Driven Real Business Cycle Hypothesis Dead?," NBER Working Papers 8726, National Bureau of Economic Research, Inc.
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