Crespo Cuaresma, Jesus, Feldkircher, Martin, Huber, Florian. 2016. Forecasting with Global Vector Autoregressive Models: A Bayesian Approach. Journal of Applied Econometrics 31 (7), 1371-1391.
BibTeX
Abstract
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 predictive 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.
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Status of publication | Published |
---|---|
Affiliation | WU |
Type of publication | Journal article |
Journal | Journal of Applied Econometrics |
Citation Index | SSCI |
WU Journalrating 2009 | A |
WU-Journal-Rating new | FIN-A, VW-B, WH-B |
Language | English |
Title | Forecasting with Global Vector Autoregressive Models: A Bayesian Approach |
Volume | 31 |
Number | 7 |
Year | 2016 |
Page from | 1371 |
Page to | 1391 |
Reviewed? | Y |
DOI | http://dx.doi.org/10.1002/jae.2504 |
Associations
- People
- Crespo Cuaresma, Jesus (Details)
- Feldkircher, Martin (Former researcher)
- Huber, Florian (Former researcher)
- Organization
- Department of Economics (Crespo Cuaresma) (Details)
- Research Institute for Human Capital and Development
FI
(Former organization)
- Competence Center for Sustainability Transformation and Responsibility WE (Details)