A new posterior sampler for Bayesian structural vector autoregressive models

Bruns, Martin and Piffer, Michele (2023) A new posterior sampler for Bayesian structural vector autoregressive models. Quantitative Economics, 14 (4). pp. 1221-1250. ISSN 1759-7331

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Abstract

We develop an importance sampler for sign restricted Bayesian structural vector autoregressive models. The algorithm nests as a special case the sampler associated with the popular Normal inverse Wishart Uniform prior, while allowing to move beyond such prior in medium sized models. We then propose a prior on contemporaneous impulse responses that provides flexibility on the magnitude and shape of the impact responses. We illustrate the quantitative relevance of the choice of the prior in an application to US monetary policy shocks. We find that the real effects of monetary policy shocks are stronger under our proposed prior than in the Normal inverse Wishart Uniform setup.

Item Type:	Article
Faculty \ School:	Faculty of Social Sciences > School of Economics
UEA Research Groups:	Faculty of Social Sciences > Research Groups > Applied Econometrics And Finance Faculty of Science > Research Groups > Statistics
Depositing User:	LivePure Connector
Date Deposited:	27 Jun 2023 09:31
Last Modified:	16 Apr 2025 00:20
URI:	https://ueaeprints.uea.ac.uk/id/eprint/92504
DOI:	10.3982/QE2207

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