Proxy VAR Models in a Data-Rich Environment

46 Pages Posted: 22 Nov 2019

See all articles by Martin Bruns

Martin Bruns

University of East Anglia (UEA)

Multiple version iconThere are 2 versions of this paper

Date Written: November 11, 2019

Abstract

Structural VAR models require two ingredients: (i) Informational sufficiency, and (ii) a valid identification strategy. These conditions are unlikely to be met by small-scale recursively identified VAR models. I propose a Bayesian Proxy Factor-Augmented VAR (BP-FAVAR) to combine a large information set with an identification scheme based on an external instrument. In an application to monetary policy shocks I find that augmenting a standard small-scale Proxy VAR by factors from a large set of financial variables changes the model dynamics and delivers price responses which are more in line with economic theory. A second application shows that an exogenous increase in uncertainty affects disaggregated investment series more negatively than consumption series.

Keywords: dynamic factor models, external instruments, monetary policy, uncertainty shocks

JEL Classification: C38, E60

Suggested Citation

Bruns, Martin, Proxy VAR Models in a Data-Rich Environment (November 11, 2019). Available at SSRN: https://ssrn.com/abstract=3484992 or http://dx.doi.org/10.2139/ssrn.3484992

Martin Bruns (Contact Author)

University of East Anglia (UEA) ( email )

Norwich Research Park
Norwich, Norfolk NR4 7TJ
United Kingdom

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