Rare Shocks, Great Recessions

52 Pages Posted: 18 Dec 2012

See all articles by Vasco Cúrdia

Vasco Cúrdia

Federal Reserve Bank of San Francisco

Marco Del Negro

Federal Reserve Bank of New York

Daniel Greenwald

Massachusetts Institute of Technology (MIT) - Sloan School of Management

Date Written: December 1, 2012

Abstract

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.

Keywords: Bayesian Analysis of DSGE Models, Fat tails, stochastic volatility, Great Recession

JEL Classification: C32, E32

Suggested Citation

Cúrdia, Vasco and Del Negro, Marco and Greenwald, Daniel, Rare Shocks, Great Recessions (December 1, 2012). FRB of New York Staff Report No. 585, Available at SSRN: https://ssrn.com/abstract=2190529 or http://dx.doi.org/10.2139/ssrn.2190529

Vasco Cúrdia

Federal Reserve Bank of San Francisco ( email )

101 Market Street
MS 1130
San Francisco, CA 94105
United States
(415) 977-3624 (Phone)

HOME PAGE: http://www.frbsf.org/economics/economists/staff.php?vcurdia

Marco Del Negro (Contact Author)

Federal Reserve Bank of New York ( email )

33 Liberty Street
New York, NY 10045
United States

Daniel Greenwald

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

77 Massachusetts Ave. E62-663
Cambridge, MA 02142
United States

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