eprintid: 13858 rev_number: 10 eprint_status: archive userid: 5 dir: disk0/00/01/38/58 datestamp: 2016-10-03 09:57:13 lastmod: 2021-08-27 17:41:36 status_changed: 2016-10-03 09:57:13 type: article metadata_visibility: show item_issues_count: 0 creators_name: Martin, F. creators_name: Crespo Cuaresma, J. creators_id: 1838 title: Weighting schemes in global VAR modelling: a forecasting exercise ispublished: pub divisions: prog_pop keywords: Global VAR modelling; forecasting; global spillovers 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. date: 2017-03 date_type: published publisher: Springer Berlin Heidelberg id_number: 10.1007/s12076-016-0170-x creators_browse_id: 58 full_text_status: public publication: Letters in Spatial and Resource Sciences volume: 10 number: 1 pagerange: 45-56 refereed: TRUE issn: 1864-4031 coversheets_dirty: FALSE fp7_project: no fp7_type: info:eu-repo/semantics/article citation: Martin, F. & Crespo Cuaresma, J. (2017). Weighting schemes in global VAR modelling: a forecasting exercise. Letters in Spatial and Resource Sciences 10 (1) 45-56. 10.1007/s12076-016-0170-x . document_url: https://pure.iiasa.ac.at/id/eprint/13858/1/Weighting%20schemes%20in%20global%20VAR%20modelling%20a%20forecasting%20exercise.pdf