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Rare shocks, Great Recessions

  • Vasco Cúrdia
  • Marco Del Negro
  • Daniel L. Greenwald

We estimate a DSGE model where rare large shocks can occur, by replacing the commonly used Gaussian assumption with a Student-t distribution. Results from the Smets and Wouters (2007) model estimated on the usual set of macroeconomic time series over the 1964-2011 period indicate that the Student-t specification is strongly favored by the data even when we allow for low-frequency variation in the volatility of the shocks, and that the estimated degrees of freedom are quite low for several shocks that drive U.S. business cycles, implying an important role for rare large shocks. This result holds even if we exclude the Great Recession period from the sample. We also show that inference about low-frequency changes in volatility and in particular, inference about the magnitude of the Great Moderation is different once we allow for fat tails.

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Paper provided by Federal Reserve Bank of San Francisco in its series Working Paper Series with number 2013-01.

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Date of creation: 2013
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Handle: RePEc:fip:fedfwp:2013-01
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  1. Edge, Rochelle M & Gürkaynak, Refet S., 2010. "How Useful Are Estimated DSGE Model Forecasts for Central Bankers?," CEPR Discussion Papers 8158, C.E.P.R. Discussion Papers.
  2. Bos, C.S. & Mahieu, R.J. & van Dijk, H.K., 1999. "Daily exchange rate behaviour and hedging of currency risk," Econometric Institute Research Papers EI 9936/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  3. Guido Ascari & Giorgio Fagiolo & Andrea Roventini, 2012. "Fat-tail Distributions and Business-Cycle Models," Documents de Travail de l'OFCE 2012-01, Observatoire Francais des Conjonctures Economiques (OFCE).
  4. Michele Boldrin & Lawrence J. Christiano & Jonas D. M. Fisher, 2000. "Habit persistence, asset returns and the business cycle," Staff Report 280, Federal Reserve Bank of Minneapolis.
  5. Zheng Liu & Daniel F. Waggoner & Tao Zha, 2010. "Sources of Macroeconomic Fluctuations: A Regime-switching DSGE Approach," Emory Economics 1002, Department of Economics, Emory University (Atlanta).
  6. Frank Smets & Raf Wouters, 2002. "An estimated dynamic stochastic general equilibrium model of the euro area," Working Paper Research 35, National Bank of Belgium.
  7. Geweke, J, 1993. "Bayesian Treatment of the Independent Student- t Linear Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages S19-40, Suppl. De.
  8. Chib, Siddhartha & Greenberg, Edward, 1994. "Bayes inference in regression models with ARMA (p, q) errors," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 183-206.
  9. Siddhartha Chib & Srikanth Ramamurthy, 2014. "DSGE Models with Student- t Errors," Econometric Reviews, Taylor & Francis Journals, vol. 33(1-4), pages 152-171, June.
  10. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
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