Forecasting with high dimensional panel VARs

Koop, Gary and Korobilis, Dimitris (2018) Forecasting with high dimensional panel VARs. Oxford Bulletin of Economics and Statistics. ISSN 1468-0084 (In Press)

[img] Text (Koop-Korobilis-OBES-2018-Forecasting-with-high-dimensional-panel)
Koop_Korobilis_OBES_2018_Forecasting_with_high_dimensional_panel.pdf
Accepted Author Manuscript
Restricted to Repository staff only until 2 October 2020.

Download (483kB) | Request a copy from the Strathclyde author

    Abstract

    This paper develops methods for estimating and forecasting in Bayesian panel vector autoregressions of large dimensions with time-varying parameters and stochastic volatility. We exploit a hierarchical prior that takes into account possible pooling restrictions involving both VAR coefficients and the error covariance matrix, and propose a Bayesian dynamic learning procedure that controls for various sources of model uncertainty. We tackle computational concerns by means of a simulation-free algorithm that relies on an analytical approximation of the posterior distribution. We use our methods to forecast inflation rates in the eurozone and show that forecasts from our flexible specification are superior to alternative methods for large vector autoregressions.