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Does Joint Modelling of the World Economy Pay Off? Evaluating Global Forecasts from a Bayesian GVAR

Dovern, Jonas ; Feldkircher, Martin ; Huber , Florian

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We analyze how modeling international dependencies improves forecasts for the global economy based on a Bayesian GVAR with SSVS prior and stochastic volatility. To analyze the source of performance gains, we decompose the predictive joint density into its marginals and a copula term capturing the dependence structure across countries. The GVAR outperforms forecasts based on country-specific models. This performance is solely driven by superior predictions for the dependence structure across countries, whereas the GVAR does not yield better predictive marginal densities. The relative performance gains of the GVAR model are particularly pronounced during volatile periods and for emerging economies.

Item Type: Working paper
Series Name: Discussion Paper Series, University of Heidelberg, Department of Economics
Volume: 0590
Place of Publication: Heidelberg
Date Deposited: 27 Mar 2015 13:07
Date: March 2015
Faculties / Institutes: The Faculty of Economics and Social Studies > Alfred-Weber-Institut for Economics
Subjects: 330 Economics
Uncontrolled Keywords: GVAR, global economy, forecast evaluation, log score, copula
Schriftenreihe ID: Discussion Paper Series / University of Heidelberg, Department of Economics
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