| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP12532 |
| DP12532 Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks | |
| Christiane Baumeister; James Hamilton | |
| 发表日期 | 2017-12-22 |
| 出版年 | 2017 |
| 语种 | 英语 |
| 摘要 | Traditional approaches to structural vector autoregressions can be viewed as special cases of Bayesian inference arising from very strong prior beliefs. These methods can be generalized with a less restrictive formulation that incorporates uncertainty about the identifying assumptions themselves. We use this approach to revisit the importance of shocks to oil supply and demand. Supply disruptions turn out to be a bigger factor in historical oil price movements and inventory accumulation a smaller factor than implied by earlier estimates. Supply shocks lead to a reduction in global economic activity after a significant lag, whereas shocks to oil demand do not. |
| 主题 | International Macroeconomics and Finance |
| 关键词 | Oil prices Vector autoregressions Sign restrictions Measurement error Bayesian inference |
| URL | https://cepr.org/publications/dp12532 |
| 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/541343 |
| 推荐引用方式 GB/T 7714 | Christiane Baumeister,James Hamilton. DP12532 Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks. 2017. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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