Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/127407
Authors: 
Dovern, Jonas
Feldkircher, Martin
Huber , Florian
Year of Publication: 
2015
Series/Report no.: 
Discussion Paper Series, University of Heidelberg, Department of Economics 590
Abstract: 
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.
Subjects: 
GVAR
global economy
forecast evaluation
log score
copula
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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