Predictive Density Aggregation: A Model for Global GDP Growth
34 Pages Posted: 30 Jun 2020
Date Written: May 1, 2020
In this paper we propose a novel approach to obtain the predictive density of global GDP growth. It hinges upon a bottom-up probabilistic model that estimates and combines single countries' predictive GDP growth densities, taking into account cross-country interdependencies. Specifically,we model non-parametrically the contemporaneous interdependencies across the United States,the euro area, and China via a conditional kernel density estimation of a joint distribution. Then, we characterize the potential amplification effects stemming from other large economies in each region-also with kernel density estimations-and the reaction of all other economies with para-metric assumptions. Importantly, each economy's predictive density also depends on a set of observable country-specific factors. Finally, the use of sampling techniques allows us to aggregate individual countries' densities into a world aggregate while preserving the non-i.i.d. nature of the global GDP growth distribution. Out-of-sample metrics con?rm the accuracy of our approach.
Keywords: Real effective exchange rates, Indicators of economic activity, Economic growth, Economic indicators, Economic policy, Density aggregation, density evaluation, global GDP growth, predictive density., WP, euro area, GDP growth, country-specific, joint density, regional leader
JEL Classification: C12, E17, E37, E01, G21, C43, H61, O24
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