| 来源类型 | Article |
| 规范类型 | 其他 |
| DOI | 10.1002/jae.2504 |
| Forecasting with Global Vector Autoregressive Models: a Bayesian Approach. | |
| Crespo Cuaresma J; Feldkircher M; Huber F | |
| 发表日期 | 2016 |
| 出处 | Journal of Applied Econometrics 31 (7): 1371-1391 |
| 出版年 | 2016 |
| 语种 | 英语 |
| 摘要 | 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. |
| 主题 | World Population (POP) |
| URL | http://pure.iiasa.ac.at/id/eprint/11918/ |
| 来源智库 | International Institute for Applied Systems Analysis (Austria) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/130559 |
| 推荐引用方式 GB/T 7714 | Crespo Cuaresma J,Feldkircher M,Huber F. Forecasting with Global Vector Autoregressive Models: a Bayesian Approach.. 2016. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Forecasting%20with%2（690KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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