BVAR-package {BVAR}R Documentation

BVAR: Hierarchical Bayesian vector autoregression

Description

Estimation of hierarchical Bayesian vector autoregressive models following Kuschnig & Vashold (2021). 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.

References

Giannone, D. and Lenza, M. and Primiceri, G. E. (2015) Prior Selection for Vector Autoregressions. The Review of Economics and Statistics, 97:2, 436-451, doi: 10.1162/REST_a_00483.

Kuschnig, N. and Vashold, L. (2021) BVAR: Bayesian Vector Autoregressions with Hierarchical Prior Selection in R. Journal of Statistical Software, 14, 1-27, doi: 10.18637/jss.v100.i14.


[Package BVAR version 1.0.2 Index]