Prior selection for panel vector autoregressions

There is a vast literature that speci…es Bayesian shrinkage priors for vector autoregressions (VARs) of possibly large dimensions. In this paper I argue that many of these priors are not appropriate for multi-country settings, which motivates me to develop priors for panel VARs (PVARs). The parametric and semi-parametric priors I suggest not only perform valuable shrinkage in large dimensions, but also allow for soft clustering of variables or countries which are homogeneous. I discuss the implications of these new priors for modelling interdependencies and heterogeneities among di¤erent countries in a panel VAR setting. Monte Carlo evidence and an empirical forecasting exercise show clear and important gains of the new priors compared to existing popular priors for VARs and PVARs. Keywords: Bayesian model selection; shrinkage; spike and slab priors; forecasting; large vector autoregression JEL Classi…cation: C11, C33, C52 Adam Smith Business School, University of Glasgow, Room 204c Gilbert Scott building, Glasgow, G12 8QQ, United Kingdom. Tel: +44 (0)141 33