| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP15245 |
| DP15245 How to Estimate a VAR after March 2020 | |
| Michele Lenza; Giorgio Primiceri | |
| 发表日期 | 2020-09-01 |
| 出版年 | 2020 |
| 语种 | 英语 |
| 摘要 | This paper illustrates how to handle a sequence of extreme observations---such as those recorded during the COVID-19 pandemic---when estimating a Vector Autoregression, which is the most popular time-series model in macroeconomics. Our results show that the ad-hoc strategy of dropping these observations may be acceptable for the purpose of parameter estimation. However, disregarding these recent data is inappropriate for forecasting the future evolution of the economy, because it vastly underestimates uncertainty. |
| 主题 | Monetary Economics and Fluctuations |
| 关键词 | Covid-19 Volatility Outliers Density forecasts |
| URL | https://cepr.org/publications/dp15245 |
| 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/544220 |
| 推荐引用方式 GB/T 7714 | Michele Lenza,Giorgio Primiceri. DP15245 How to Estimate a VAR after March 2020. 2020. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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