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Finance and Economics Discussion Series: Computing DSGE Models with Recursive Preferences and Stochastic Volatility - Tapa blanda

Caldara, Dario

 
9781288697380: Finance and Economics Discussion Series: Computing DSGE Models with Recursive Preferences and Stochastic Volatility
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ISBN 10: 1288697384 ISBN 13: 9781288697380
Editorial: BiblioGov, 2013

Sinopsis

This paper compares different solution methods for computing the equilibrium of dynamic stochastic general equilibrium (DSGE) models with recursive preferences such as those in Epstein and Zin (1989 and 1991) and stochastic volatility. Models with these two features have recently become popular, but we know little about the best ways to implement them numerically. To fill this gap, we solve the stochastic neoclassical growth model with recursive preferences and stochastic volatility using four different approaches: second- and third-order perturbation, Chebyshev polynomials, and value function iteration. We document the performance of the methods in terms of computing time, implementation complexity, and accuracy. Our main finding is that perturbations are competitive in terms of accuracy with Chebyshev polynomials and value function iteration while being several orders of magnitude faster to run. Therefore, we conclude that perturbation methods are an attractive approach for computing this class of problems.

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Reseña del editor

This paper compares different solution methods for computing the equilibrium of dynamic stochastic general equilibrium (DSGE) models with recursive preferences such as those in Epstein and Zin (1989 and 1991) and stochastic volatility. Models with these two features have recently become popular, but we know little about the best ways to implement them numerically. To fill this gap, we solve the stochastic neoclassical growth model with recursive preferences and stochastic volatility using four different approaches: second- and third-order perturbation, Chebyshev polynomials, and value function iteration. We document the performance of the methods in terms of computing time, implementation complexity, and accuracy. Our main finding is that perturbations are competitive in terms of accuracy with Chebyshev polynomials and value function iteration while being several orders of magnitude faster to run. Therefore, we conclude that perturbation methods are an attractive approach for computing this class of problems.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
BiblioGov
Año de publicación
2013
Idioma
Inglés
ISBN 10 
1288697384
ISBN 13 
9781288697380
Encuadernación
Tapa blanda
Número de páginas
48
Contacto del fabricante
no disponible
Persona responsable
no disponible