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Occasionally binding constraints in large models : a review of solution methods / by Jonathan Swarbrick. : FB3-6/2021-5E-PDF

"This practical review assesses several approaches to solving medium- and large-scale dynamic stochastic general equilibrium (DSGE) models featuring occasionally binding constraints. In such models, global solution methods are not possible because of the curse of dimensionality. This causes the modeller to look elsewhere for methods that can handle the significant non-linearities and non-differentiable functions that inequality constraints represent. The paper discusses methods-including Newton-type solvers under perfect foresight, the piecewise linear algorithm (OccBin), regime-switching models (RISE) and the news shocks approach (DynareOBC) - and compares the results from a simple borrowing constraints model obtained using projection methods, providing example MATLAB code. The study focuses on the news shocks method, which I find produces higher accuracy than other methods and allows the modeller to study multiple equilibria and determinacy issues"--Abstract, page ii.

Lien permanent pour cette publication :
publications.gc.ca/pub?id=9.903072&sl=1

Renseignements sur la publication
Ministère/Organisme
  • Bank of Canada, issuing body.
TitreOccasionally binding constraints in large models : a review of solution methods / by Jonathan Swarbrick.
Titre de la série
  • Staff discussion paper = Document d'analyse du personnel, 1914-0568 ; 2021-5
Type de publicationMonographie - Voir l'enregistrement principal
Langue[Anglais]
FormatTexte numérique
Document électronique
Note(s)
  • Cover title.
  • "March 23, 2021."
  • Includes bibliographical references (pages 42-47).
Information sur la publication
  • Ottawa, Ontario, Canada : Bank of Canada = Banque du Canada, 2021.
  • ©2021
Auteur / Contributeur
  • Swarbrick, Jonathan M., author.
Description1 online resource (ii, 47 pages) : graphs.
Numéro de catalogue
  • FB3-6/2021-5E-PDF
Descripteurs
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