Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/127407 
Erscheinungsjahr: 
2015
Schriftenreihe/Nr.: 
Discussion Paper Series No. 590
Verlag: 
University of Heidelberg, Department of Economics, Heidelberg
Zusammenfassung: 
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.
Schlagwörter: 
GVAR
global economy
forecast evaluation
log score
copula
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Dokumentart: 
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