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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, but replace the commonly used Gaussian assumption with a Student´s 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 1) the Student´s t specification is strongly favored by the data, even when we allow for low-frequency variation in the volatility of the shocks, and 2) 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 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 New York in its series Staff Reports with number 585.

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Date of creation: 2012
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Handle: RePEc:fip:fednsr:585
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  1. Guido Ascari & Giorgio Fagiolo & Andrea Roventini, 2012. "Fat-Tail Distributions and Business-Cycle Models," LEM Papers Series 2012/02, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  2. Michele Boldrin & Lawrence J. Christiano & Jonas D.M. Fisher, 1999. "Habit persistence, asset returns and the business cycles," Working Paper Series WP-99-14, Federal Reserve Bank of Chicago.
  3. Bos, C.S. & Mahieu, R.J. & van Dijk, H.K., 2000. "Daily exchange rate behaviour and hedging of currency risk," Econometric Institute Research Papers EI 2000-25/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  4. Siddhartha Chib & Srikanth Ramamurthy, 2014. "DSGE Models with Student- t Errors," Econometric Reviews, Taylor & Francis Journals, vol. 33(1-4), pages 152-171, June.
  5. 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.
  6. Zheng Liu & Daniel F. Waggoner & Tao Zha, 2011. "Sources of macroeconomic fluctuations: A regime‐switching DSGE approach," Quantitative Economics, Econometric Society, vol. 2(2), pages 251-301, 07.
  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. 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. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
  10. 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.
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