Dovern, Jonas ; Feldkircher, Martin ; Huber , Florian
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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.
Document type: | Working paper |
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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 |
DDC-classification: | 330 Economics |
Uncontrolled Keywords: | GVAR, global economy, forecast evaluation, log score, copula |
Series: | Discussion Paper Series / University of Heidelberg, Department of Economics |