SVARs Identification Through Bounds on the Forecast Error Variance

Bibliographic Data

ID19418893
AuthorsAlessio Volpicella (0000-0002-8108-2655, University of Surrey, corresponding author)
Year2022
Volume40
Issue3
Pages1291-1301
Publication date2022-07-03
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueJournal of Business and Economic Statistics (JOURNAL)
Journal identifiersISSN: 0735-0015 • E-ISSN: 1537-2707
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/07350015.2021.1927742
OpenAlexW3160964261
LanguageEN
Citations received3
References cited38

This article identifies structural vector autoregressions (SVARs) through bound restrictions on the forecast error variance decomposition (FEVD). First, the article shows FEVD bounds correspond to quadratic inequality restrictions on the columns of the rotation matrix transforming reduced-form residuals into structural shocks. Second, the article establishes theoretical conditions such that bounds on the FEVD lead to a reduction in the width of the impulse response identified set relative to only imposing sign restrictions. Third, this article proposes a robust Bayesian approach to inference. Fourth, the article shows that elicitation of the bounds could be based on DSGE models with alternative parameterizations. Finally, an empirical application illustrates the potential usefulness of FEVD restrictions for obtaining informative inference in set-identified monetary SVARs and remove unreasonable implications of models identified through sign restrictions

Bayesian probability · Dynamic stochastic general equilibrium · Econometrics · Economics · Impulse response · Inference · Mathematical optimization · Monetary policy · Quadratic equation · Statistics · Upper and lower bounds · Variance decomposition of forecast errors · Computer Science · Forecasting Techniques and Applications · Market Dynamics and Volatility · Mathematics · Monetary Policy and Economic Impact

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