Model Uncertainty in Panel Vector Autoregressive Models

Gary Koop and Dimitris Korobilis

No 2014-011, SIRE Discussion Papers from Scottish Institute for Research in Economics (SIRE)

Abstract: We develop methods for Bayesian model averaging (BMA) or selection (BMS) in Panel Vector Autoregressions (PVARs). Our approach allows us to select between or average over all possible combinations of restricted PVARs where the restrictions involve interdependencies between and heterogeneities across cross-sectional units. The resulting BMA framework can find a parsimonious PVAR specification, thus dealing with overparameterization concerns. We use these methods in an application involving the euro area sovereign debt crisis and show that our methods perform better than alternatives. Our findings contradict a simple view of the sovereign debt crisis which divides the euro zone into groups of core and peripheral countries and worries about financial contagion within the latter group.

Keywords: Bayesian model averaging; stochastic search variable selection; financial contagion; sovereign debt crisis (search for similar items in EconPapers)
Date: 2014-08
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Citations: View citations in EconPapers (2)

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Related works:
Journal Article: Model uncertainty in Panel Vector Autoregressive models (2016)
Working Paper: Model Uncertainty in Panel Vector Autoregressive Models (2015)
Working Paper: Model uncertainty in panel vector autoregressive models (2014)
Working Paper: Model Uncertainty in Panel Vector Autoregressive Models (2014)
Working Paper: Model Uncertainty in Panel Vector Autoregressive Models (2014)
Working Paper: Model uncertainty in panel vector autoregressive models (2014)
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