Advances in Using Vector Autoregressions to Estimate Structural Magnitudes

This paper discusses drawing structural conclusions from vector autoregressions. We call attention to a common error in estimating structural elasticities and show how to correctly estimate elasticities even in the case when one knows only the effects of a single structural shock and the covariance matrix of the reduced-form residuals. We describe the traditional approach to identification as a claim to have exact prior information about the structural model and propose Bayesian inference as a way to acknowledge that prior information is imperfect or subject to error. We raise concerns about the way that results are typically reported for VARs that are set-identified using sign and other restrictions.

09. December 2021

Authors Christiane Baumeister James D. Hamilton

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Professor Christiane Baumeister, PhD
Professor Christiane Baumeister, PhD

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