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Rare Shocks, Great Recessions

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  • Marco Del Negro

    (Federal Reserve Bank of New York)

  • Vasco Curdia

    (Federal Reserve Bank of New York)

Abstract

We estimate a DSGE model where rare large shocks can occur, by replacing the commonly used Gaussian assumption with a Student-t distribution. We show that the latter is favored by the data in the context of a Smets and Wouters-type model estimated on macro variables, even if we allow for low frequency variation in the shocks' volatility. The evidence is even stronger when we introduce financial frictions as in Bernanke, Gertler and Gilchrist (1999), and correspondingly include a measure of interest rate spreads among the observables. We provide some evidence that introducing Student-t shocks reduces the importance of low-frequency time-variation in volatility. In particular, we show that the Great Recession of 2008-09 does not result in significant increases in estimated time-varying volatility (i.e., it is not a reversal of the Great Moderation) but is largely the outcome of large shocks.

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Bibliographic Info

Paper provided by Society for Economic Dynamics in its series 2012 Meeting Papers with number 654.

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Date of creation: 2012
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Handle: RePEc:red:sed012:654

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  1. 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.
  2. 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).
  3. Charles S. Bos & Ronald J. Mahieu & Herman K. van Dijk, 1999. "Daily Exchange Rate Behaviour and Hedging of Currency Risk," Tinbergen Institute Discussion Papers 99-078/4, Tinbergen Institute.
  4. Lawrence J. Christiano & Michele Boldrin & Jonas D. M. Fisher, 2001. "Habit Persistence, Asset Returns, and the Business Cycle," American Economic Review, American Economic Association, vol. 91(1), pages 149-166, March.
  5. Frank Smets & Raf Wouters, 2003. "An Estimated Dynamic Stochastic General Equilibrium Model of the Euro Area," Journal of the European Economic Association, MIT Press, vol. 1(5), pages 1123-1175, 09.
  6. 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).
  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. Rochelle M. Edge & Refet S. Gurkaynak, 2010. "How Useful Are Estimated DSGE Model Forecasts for Central Bankers?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 41(2 (Fall)), pages 209-259.
  9. 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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  1. Rare shocks, Great Recessions
    by Christian Zimmermann in NEP-DGE blog on 2013-03-03 00:49:08
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Cited by:
  1. Ching-Wai (Jeremy) Chiu & Haroon Mumtaz & Gabor Pinter, 2014. "Fat-tails in VAR Models," Working Papers 714, Queen Mary, University of London, School of Economics and Finance.
  2. Giorgio Fagiolo & Andrea Roventini, 2012. "Macroeconomic Policy in DSGE and Agent-Based Models," EconomiX Working Papers 2012-17, University of Paris West - Nanterre la Défense, EconomiX.
  3. Todd E. Clark & Francesco Ravazzolo, 2012. "The macroeconomic forecasting performance of autoregressive models with alternative specifications of time-varying volatility," Working Paper 2012/09, Norges Bank.
  4. Marco Del Negro & Giorgio Primiceri, 2013. "Time-varying structural vector autoregressions and monetary policy: a corrigendum," Staff Reports 619, Federal Reserve Bank of New York.

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