Dear R users,
please let me draw your attention to my new R package bvarsv (on CRAN
since August 28) which implements the Primiceri (Review of Economic
Studies, 2005) vector autoregressive model. The model is popular in
macroeconomic analysis as it allows to model instabilities (e.g. in the
mean and volatility dynamics) that are often observed in macroeconomic
time series like inflation.
The package provides functionality for Bayesian analysis of the
Primiceri model. To the best of my knowledge, it is the only publicly
available R code to do so. The underlying Markov Chain Monte Carlo
algorithm is computationally challenging, since each iteration requires
multiple calls of a recursive Kalman filter type algorithm. Therefore,
bvarsv relies on C++ code ported to R via Rcpp and RcppArmadillo. The
clear focus of the package is on forecasting, as opposed to structural
analysis of economic relationships. The package allows to compute
posterior predictive distributions, which can then be plotted and
analyzed using forecast evaluation techniques. More detailed
documentation and examples is available here:
https://sites.google.com/site/fk83research/code
Your feedback on any aspects of the package, as well as possible
improvements or extensions, would be highly appreciated.
Thank you and best wishes,
Fabian Krüger
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