| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP15109 |
| DP15109 Modeling and Forecasting Macroeconomic Downside Risk | |
| Davide Delle Monache; Andrea De Polis; Ivan Petrella | |
| 发表日期 | 2022-02-17 |
| 出版年 | 2022 |
| 语种 | 英语 |
| 摘要 | We model permanent and transitory changes of the predictive density of US GDP growth. A substantial increase in downside risk to US economic growth emerges over the last 30 years, associated with the long-run growth slowdown started in the early 2000s. Conditional skewness moves procyclically, implying negatively skewed predictive densities ahead and during recessions, often anticipated by deteriorating financial conditions. Conversely, positively skewed distributions characterize expansions. The modelling framework ensures robustness to tail events, allows for both dense or sparse predictor designs, and delivers competitive out-of-sample (point, density and tail) forecasts, improving upon standard benchmarks. |
| 主题 | Monetary Economics and Fluctuations |
| 关键词 | Business cycle Downside risk Skewness Score driven models Financial conditions |
| URL | https://cepr.org/publications/dp15109-3 |
| 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/545997 |
| 推荐引用方式 GB/T 7714 | Davide Delle Monache,Andrea De Polis,Ivan Petrella. DP15109 Modeling and Forecasting Macroeconomic Downside Risk. 2022. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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