Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/330775 
Year of Publication: 
2024
Citation: 
[Journal:] Computational Economics [ISSN:] 1572-9974 [Volume:] 66 [Issue:] 1 [Publisher:] Springer US [Place:] New York, NY [Year:] 2024 [Pages:] 593-643
Publisher: 
Springer US, New York, NY
Abstract: 
This paper presents and compares Bernoulli iterative approaches for solving linear DSGE models. The methods are compared using 99 different models from the macroeconomic model data base (MMB) and different parameterizations of the monetary policy rule in the medium-scale new Keynesian model of Smets and Wouters (Am Econ Rev 97(3):586–606, 2007. https://doi.org/10.1257/aer.97.3.586 ) iteratively. I find that Bernoulli methods providing similar accuracy as measured by the forward error of the solution at a somewhat higher computation burden to the standard method of Dynare when solving DSGE models. The method, however, has convergence properties useful when a specific solution, e.g., unique stable, is sought and can be combined with other iterative methods, such as the Newton method, lending themselves especially to refining solutions—either when standard methods fail or when one moves through a parameter space iteratively—as I show in applications of the methods.
Subjects: 
Functional iteration
Numerical accuracy
DSGE
Solution methods
JEL: 
C61
C63
E17
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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