Solution Methods for Models with Rare Disasters

Jesus Fernandez-Villaverde and Oren Levintal

No 21997, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: This paper compares different solution methods for computing the equilibrium of dynamic stochastic general equilibrium (DSGE) models with rare disasters along the line of those proposed by Rietz (1988), Barro (2006}, Gabaix (2012), and Gourio (2012). DSGE models with rare disasters require solution methods that can handle the large non-linearities triggered by low-probability, high-impact events with sufficient accuracy and speed. We solve a standard New Keynesian model with Epstein-Zin preferences and time-varying disaster risk with perturbation, Taylor projection, and Smolyak collocation. Our main finding is that Taylor projection delivers the best accuracy/speed tradeoff among the tested solutions. We also document that even third-order perturbations may generate solutions that suffer from accuracy problems and that Smolyak collocation can be costly in terms of run time and memory requirements.

JEL-codes: C63 C68 E32 E37 E44 G12 (search for similar items in EconPapers)
Date: 2016-02
New Economics Papers: this item is included in nep-dge, nep-mac and nep-ore
Note: EFG
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Citations: View citations in EconPapers (16)

Published as Jesús Fernández-Villaverde & Oren Levintal, 2018. "Solution methods for models with rare disasters," Quantitative Economics, vol 9(2), pages 903-944.

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Journal Article: Solution methods for models with rare disasters (2018)
Working Paper: Solution Methods for Models with Rare Disasters (2016)
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