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Regular version of the site

Article

Картографирование BVAR

Прикладная эконометрика. 2016. Т. 43. С. 118-141.

This paper reviews estimation and forecasting with Bayesian vector autoregressions (BVARs). In the first part of the paper, we propose a clear classification of the most frequently used prior distributions and we show how the parameters of posterior distributions can be computed for the priors  we consider in the paper.   A separate section describes the endogenous choice of prior  hyperparameters that is currently a key step to estimate a BVAR in a data-rich environment.

The second part of this paper is devoted to forecasting with BVARs. We review both point and density forecasting.

We also developed a package bvarr for statistical environment R with the same notations as in this review. The bvarr package can be freely used for research and educational purposes.