Structural Gaussian mixture vector autoregressive model with application to the asymmetric effects of monetary policy shocks

Fuente: arXiv
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Main Author: Virolainen, Savi
Format: Preprint
Published: 2020
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author Virolainen, Savi
author_facet Virolainen, Savi
contents A structural Gaussian mixture vector autoregressive model is introduced. The shocks are identified by combining simultaneous diagonalization of the reduced form error covariance matrices with constraints on the time-varying impact matrix. This leads to flexible identification conditions, and some of the constraints are also testable. The empirical application studies asymmetries in the effects of the U.S. monetary policy shock and finds strong asymmetries with respect to the sign and size of the shock and to the initial state of the economy. The accompanying CRAN distributed R package gmvarkit provides a comprehensive set of tools for numerical analysis.
format Preprint
id arxiv_https___arxiv_org_abs_2007_04713
institution arXiv
publishDate 2020
record_format arxiv
spellingShingle Structural Gaussian mixture vector autoregressive model with application to the asymmetric effects of monetary policy shocks
Virolainen, Savi
Econometrics
Methodology
62M10
A structural Gaussian mixture vector autoregressive model is introduced. The shocks are identified by combining simultaneous diagonalization of the reduced form error covariance matrices with constraints on the time-varying impact matrix. This leads to flexible identification conditions, and some of the constraints are also testable. The empirical application studies asymmetries in the effects of the U.S. monetary policy shock and finds strong asymmetries with respect to the sign and size of the shock and to the initial state of the economy. The accompanying CRAN distributed R package gmvarkit provides a comprehensive set of tools for numerical analysis.
title Structural Gaussian mixture vector autoregressive model with application to the asymmetric effects of monetary policy shocks
topic Econometrics
Methodology
62M10
url https://arxiv.org/abs/2007.04713