Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/253600 
Authors: 
Year of Publication: 
2021
Citation: 
[Journal:] Quantitative Economics [ISSN:] 1759-7331 [Volume:] 12 [Issue:] 3 [Publisher:] The Econometric Society [Place:] New Haven, CT [Year:] 2021 [Pages:] 869-901
Publisher: 
The Econometric Society, New Haven, CT
Abstract: 
Unlike linear ones, nonlinear business cycle models can generate sustained fluctuations even in the absence of shocks (e.g., via limit cycles/chaos). A popular approach to solving nonlinear models is perturbation methods. I show that, as typically implemented, these methods are incapable of finding solutions featuring limit cycles or chaos. Fundamentally, solutions are only required not to explode, while standard perturbation algorithms seek solutions that meet the stronger requirement of convergence to the steady state. I propose a modification to standard algorithms that does not impose this overly strong requirement.
Subjects: 
chaos
computational methods
Dynamic equilibrium economies
limit cycles
nonlinear solution methods
JEL: 
C63
C68
E37
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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