Does Joint Modelling of the World Economy Pay Off? Evaluating Global Forecasts from a Bayesian GVAR
Jonas Dovern (),
Martin Feldkircher and
Working Papers from Oesterreichische Nationalbank (Austrian Central Bank)
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.
Keywords: GVAR; global economy; forecast evaluation; log score; copula (search for similar items in EconPapers)
JEL-codes: C53 E37 F47 (search for similar items in EconPapers)
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Journal Article: Does joint modelling of the world economy pay off? Evaluating global forecasts from a Bayesian GVAR (2016)
Working Paper: Does Joint Modelling of the World Economy Pay Off? Evaluating Global Forecasts from a Bayesian GVAR (2015)
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