11918 14 51955 3 141508 document 51955 Forecasting with global vector autoregressive models.pdf application/pdf 8778b9891bf14cba1376f1d5a8bc2b5f MD5 707070 2016-05-02 06:45:55 https://pure.iiasa.ac.at/id/eprint/11918/1/Forecasting%20with%20global%20vector%20autoregressive%20models.pdf 11918 1 1 application/pdf text en public cc_by

Forecasting with global vector autoregressive models.pdf

accepted 51956 2 141511 document 51956 lightbox.jpg image/png f22a785a320d4441aa804cc736c0e29a MD5 29530 2016-05-02 06:55:58 https://pure.iiasa.ac.at/id/eprint/11918/2/lightbox.jpg 11918 2 2 image/png other Thumbnails conversion from text to thumbnail_lightbox en staffonly

lightbox.jpg

http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/51955 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/51955 http://eprints.org/relation/islightboxThumbnailVersionOf https://pure.iiasa.ac.at/id/document/51955 51957 2 141512 document 51957 preview.jpg image/png 6dc1bde11751bf120dea72574a1a6c0d MD5 11642 2016-05-02 06:55:58 https://pure.iiasa.ac.at/id/eprint/11918/3/preview.jpg 11918 3 3 image/png other Thumbnails conversion from text to thumbnail_preview en staffonly

preview.jpg

http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/51955 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/51955 http://eprints.org/relation/ispreviewThumbnailVersionOf https://pure.iiasa.ac.at/id/document/51955 51958 2 141513 document 51958 medium.jpg image/png c24431b2a5fa061fa81681ae5594e9cf MD5 5266 2016-05-02 06:55:59 https://pure.iiasa.ac.at/id/eprint/11918/4/medium.jpg 11918 4 4 image/png other Thumbnails conversion from text to thumbnail_medium en staffonly

medium.jpg

http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/51955 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/51955 http://eprints.org/relation/ismediumThumbnailVersionOf https://pure.iiasa.ac.at/id/document/51955 51959 2 141514 document 51959 small.jpg image/png b9c2b86ff9ba2e6574feafc50eec18bb MD5 1233 2016-05-02 06:56:00 https://pure.iiasa.ac.at/id/eprint/11918/5/small.jpg 11918 5 5 image/png other Thumbnails conversion from text to thumbnail_small en staffonly

small.jpg

http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/51955 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/51955 http://eprints.org/relation/issmallThumbnailVersionOf https://pure.iiasa.ac.at/id/document/51955 51960 1 141515 document 51960 indexcodes.txt text/x-c++ 1097ad1c2adf3e0274c77714f9c6279b MD5 13022 2016-05-02 06:56:02 https://pure.iiasa.ac.at/id/eprint/11918/6/indexcodes.txt 11918 6 6 text/x-c++ other Generate index codes conversion from text to indexcodes en staffonly

indexcodes.txt

http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/51955 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/51955 http://eprints.org/relation/isIndexCodesVersionOf https://pure.iiasa.ac.at/id/document/51955 archive 353 disk0/00/01/19/18 2016-02-15 09:14:18 2021-08-27 17:40:10 2016-02-15 09:14:18 article show Crespo Cuaresma J. 1838 Feldkircher M. Huber F. pub prog_pop This paper develops a Bayesian variant of global vector autoregressive (B-GVAR) models to forecast an international set of macroeconomic and financial variables. We propose a set of hierarchical priors and compare the predicive performance of B-GVAR models in terms of point and density forecasts for one-quarter-ahead and four-quarter-ahead forecast horizons. We find that forecasts can be improved by employing a global framework and hierarchical priors which induce country-specific degrees of shrinkage on the coefficients of the GVAR model. Forecasts from various B-GVAR specifications tend to outperform forecasts from a naive univariate model, a global model without shrinkage on the parameters and country-specific vector autoregressions. 2016-11 published Wiley-Blackwell 10.1002/jae.2504 58 public Journal of Applied Econometrics 31 7 1371-1391 TRUE 1099-1255 FALSE no info:eu-repo/semantics/article