Картографирование BVAR

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

Demeshev B., Malakhovskaya O. A.

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.

Keywords: BVAR, BVAR, priors, point forecasting, density forecasting, априорные распределения, точечное прогнозирование, прогнозирование плотности

Publication based on the results of: ­­­Fiscal and monetary policy under economic and financial instability (2016)