| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP8755 |
| DP8755 Prior Selection for Vector Autoregressions | |
| Domenico Giannone; Michele Lenza; Giorgio Primiceri | |
| 发表日期 | 2012 |
| 出版年 | 2012 |
| 语种 | 英语 |
| 摘要 | Vector autoregressions (VARs) are flexible time series models that can capture complex dynamic interrelationships among macroeconomic variables. However, their dense parameterization leads to unstable inference and inaccurate out-of-sample forecasts, particularly for models with many variables. A potential solution to this problem is to use informative priors, in order to shrink the richly parameterized unrestricted model towards a parsimonious naïve benchmark, and thus reduce estimation uncertainty. This paper studies the optimal choice of the informativeness of these priors, which we treat as additional parameters, in the spirit of hierarchical modeling. This approach is theoretically grounded, easy to implement, and greatly reduces the number and importance of subjective choices in the setting of the prior. Moreover, it performs very well both in terms of out-of-sample forecasting, and accuracy in the estimation of impulse response functions. |
| 主题 | International Macroeconomics |
| 关键词 | Bayesian methods Forecasting Hierarchical modeling Impulse responses Marginal likelihood |
| URL | https://cepr.org/publications/dp8755 |
| 来源智库 | Centre for Economic Policy Research (United Kingdom) |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/537591 |
| 推荐引用方式 GB/T 7714 | Domenico Giannone,Michele Lenza,Giorgio Primiceri. DP8755 Prior Selection for Vector Autoregressions. 2012. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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