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Bayesian Macroeconometrics in R

BMR (Bayesian Macroeconometrics in R) is a collection of R and C++ routines for estimating Bayesian Vector Autoregressive (BVAR) and Dynamic Stochastic General Equilibrium (DSGE) models in the R statistical environment. For the former, BMR includes the the well-known Minnesota and normal-inverse-Wishart priors, along with Mattias Villani's steady-state prior, and allows for estimation of BVARs with time-varying parameters.

Important License Information: BMR is licensed for use at a degree-granting institution (i.e., under the user's capacity at a degree-granting institution) under the General Public License (GPL) version 3. The experimental nature of this software means that it is intended for academic use only.

By downloading, installing, and/or using the software, you agree to these terms, to the terms of the GPL v3 license, and release me from any liability arising whatsoever from use of this software.

Package requirements: the latest versions of R (v2.15, or above), Rcpp, RcppArmadillo, ggplot2, and grid (this comes pre-packaged with new R releases). Running the following commands, post installation of R itself, should be sufficient:

install.packages("RcppArmadillo")
install.packages("ggplot2")

Warning: the use of C++ code greatly reduces the computational burden of estimating the models supported by BMR, but its use will also lock the user out of the R terminal while the code is running; that is, the 'stop' command will not work, and the user will either have to wait for estimation to finish or force-quit out of the R environment. For this reason, it is suggested to first run estimation with a relatively low number of replications, then increase as required. I strongly recommend doing so when using the 'BVARTVP' function.

Download

Current version: 0.1.1, 08/19/2012.

  • Windows binary files: link.
  • Mac binary files: link.
  • Accompanying vignette: link.

The vignette (linked above) is intended to be a comprehensive guide to the routines (and what goes on under the bonnet, so to speak) and should be consulted first before submitting any questions to me about the package. I am more than happy to receive bug reports (and comments in general) about BMR, use the contact tab above to do so, but I am not willing to provide technical support for the package. (Technical support in the sense of 'how do I get my model into the required format', or 'what prior should I use'.)

After installing the package, the user can check if everything is working as intended by typing:

library(BMR)
data(BMRVARData)

This should load BMR and place a dataframe called 'USMacroData' into the workspace.

Replication files.

  • Estimate the basic New-Keynesian model: link.
  • Solve the basic New-Keynesian model: link.
  • Solve the RBC model: link.

Release notes:

  • Version 0.1.1:
    • Several minor bug fixes;
    • improvements to the help documentation; and
    • inclusion of the artificial VAR data used in sections 6.1 and 6.3 of the vignette.
  • Version 0.1: First release.