Dealing with heterogeneity in panel VARs using sparse finite mixtures

Florian Huber

No 262, Department of Economics Working Paper Series from WU Vienna University of Economics and Business

Abstract: In this paper, we provide a parsimonious means of estimating panel VARs with stochastic volatility. We assume that coefficients associated with domestic lagged endogenous variables arise from a finite mixture of Gaussian distribution. Shrinkage on the cluster size is introduced through suitable priors on the component weights and cluster-relevant quantities are identified through novel normal-gamma shrinkage priors. To assess whether dynamic interdependencies between units are needed, we moreover impose shrinkage priors on the coefficients related to other countries' endogenous variables. Finally, our model controls for static interdependencies by assuming that the reduced form shocks of the model feature a factor stochastic volatility structure. We assess the merits of the proposed approach by using synthetic data as well as a real data application. In the empirical application, we forecast Eurozone unemployment rates and show that our proposed approach works well in terms of predictions.

Keywords: multi country models; density predictions; hierarchical modeling; factor stochastic volatility models (search for similar items in EconPapers)
Date: 2018-04
New Economics Papers: this item is included in nep-ecm
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