期刊名称：Discussion Paper Series / Universität Heidelberg, Department of Economics
出版年度：2015
出版社：Universität Heidelberg, Department of Economics
摘要：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 decom- pose the predictive joint density into its marginals and a copula term cap- turing 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
关键词：GVAR; global economy; forecast evaluation; log score; copula
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