We provide a comprehensive analysis of the out-of-sample predictive
accuracy of different global vector autoregressive (GVAR) specifications based on
alternative weighting schemes to address global spillovers across countries. In addition
to weights based on bilateral trade, we entertain schemes based on different
financial variables and geodesic distance. Our results indicate that models based on
trade weights, which are standard in the literature, are systematically outperformed in
terms of predictive accuracy by other specifications. We find that, while information
on financial linkages helps improve the forecasting accuracy of GVAR models, averaging
predictions by means of simple predictive likelihood weighting does not appear
to systematically lead to lower forecast errors.
| Identifer | oai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:4958 |
| Date | 03 1900 |
| Creators | Martin, Florian, Crespo Cuaresma, Jesus |
| Publisher | Springer |
| Source Sets | Wirtschaftsuniversität Wien |
| Language | English |
| Detected Language | English |
| Type | Article, PeerReviewed |
| Format | application/pdf |
| Rights | Creative Commons: Attribution 4.0 International (CC BY 4.0) |
| Relation | http://dx.doi.org/10.1007/s12076-016-0170-x, http://epub.wu.ac.at/4958/ |
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