Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/217118
Authors: 
Fernández-Villaverde, Jesús
Levintal, Oren
Year of Publication: 
2018
Citation: 
[Journal:] Quantitative Economics [ISSN:] 1759-7331 [Volume:] 9 [Year:] 2018 [Issue:] 2 [Pages:] 903-944
Abstract: 
This paper compares different solution methods for computing the equilibrium of dynamic stochastic general equilibrium (DSGE) models with rare disasters along the lines 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 nonlinearities triggered by low-probability, high-impact events with 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.
Subjects: 
Rare disasters
DSGE models
solution methods
Taylor projection
perturbation
Smolyak
JEL: 
C63
C68
E32
E37
E44
G12
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by-nc/4.0/
Document Type: 
Article

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