Forecasting with High‐Dimensional Panel VARs. (28th February 2019)

• Record Type: Journal Article
• Authors: Koop, Gary; Korobilis, Dimitris
• Is Part Of: Oxford bulletin of economics and statistics. Volume 81:Number 5(2019)
• Page Start: 937
• Page End: 959
• Publication Date: 2019-02-28
• Subjects: Economic history -- Periodicals; Great Britain -- Economic conditions -- Periodicals; 330.9
• DOI: 10.1111/obes.12303
• Languages: English
• ISSNs: 0305-9049

Abstract

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 analytical approximations to the posterior. We use our methods to forecast inflation rates in the eurozone and show that these forecasts are superior to alternative methods for large vector autoregressions.