Quotation Martin, Florian, Crespo Cuaresma, Jesus. 2017. Weighting Schemes in Global VAR Modelling: A Forecasting Exercise. Letters in Spatial and Resource Sciences, 10 (1), 45-56.


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Abstract

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.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Letters in Spatial and Resource Sciences
Language English
Title Weighting Schemes in Global VAR Modelling: A Forecasting Exercise
Volume 10
Number 1
Year 2017
Page from 45
Page to 56
Reviewed? Y
URL http://link.springer.com/article/10.1007/s12076-016-0170-x
DOI http://dx.doi.org/10.1007/s12076-016-0170-x

Associations

People
Martin, Florian (Former researcher)
Crespo Cuaresma, Jesus (Details)
Organization
Institute for Macroeconomics IN (Details)
Institute for Economic Geography and GIScience IN (Details)
Research Institute for Human Capital and Development FI (Details)
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