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Predictive Density Aggregation: A Model for Global GDP Growth / Francesca Caselli, Francesco Grigoli, Romain Lafarguette, Changchun Wang.
- Format:
- Book
- Government document
- Author/Creator:
- Caselli, Francesca.
- Series:
- IMF Working Papers; Working Paper ; No. 2020/078
- IMF Working Papers
- Language:
- English
- Physical Description:
- 1 online resource (33 pages)
- Other Title:
- Predictive Density Aggregation
- Place of Publication:
- Washington, D.C. : International Monetary Fund, 2020.
- Summary:
- 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. Speci?cally, 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 ampli?cation e?ects 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-speci?c 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.
- Notes:
- Description based on print version record.
- ISBN:
- 9781513547633
- 1513547631
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