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BVAR: Hierarchical Bayesian Vector Autoregression
Estimation of hierarchical Bayesian vector autoregressive models following Kuschnig & Vashold (2021) <doi:10.18637/jss.v100.i14>. Implements hierarchical prior selection for conjugate priors in the fashion of Giannone, Lenza & Primiceri (2015) <doi:10.1162/REST_a_00483>. Functions to compute and identify impulse responses, calculate forecasts, forecast error variance decompositions and scenarios are available. Several methods to print, plot and summarise results facilitate analysis.
Getting started
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Package details |
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| Author | Nikolas Kuschnig [aut, cre] (<https://orcid.org/0000-0002-6642-2543>), Lukas Vashold [aut] (<https://orcid.org/0000-0002-3562-3414>), Nirai Tomass [ctb], Michael McCracken [dtc], Serena Ng [dtc] |
| Maintainer | Nikolas Kuschnig <nikolas.kuschnig@wu.ac.at> |
| License | GPL-3 | file LICENSE |
| Version | 1.0.4 |
| URL | https://github.com/nk027/bvar |
| Package repository | View on CRAN |
| Installation |
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