| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w22516 |
| 来源ID | Working Paper 22516 |
| Assessing Point Forecast Accuracy by Stochastic Error Distance | |
| Francis X. Diebold; Minchul Shin | |
| 发表日期 | 2016-08-22 |
| 出版年 | 2016 |
| 语种 | 英语 |
| 摘要 | We propose point forecast accuracy measures based directly on distance of the forecast-error c.d.f. from the unit step function at 0 ("stochastic error distance," or SED). We provide a precise characterization of the relationship between SED and standard predictive loss functions, and we show that all such loss functions can be written as weighted SED's. The leading case is absolute-error loss. Among other things, this suggests shifting attention away from conditional-mean forecasts and toward conditional-median forecasts. |
| 主题 | Econometrics ; Estimation Methods |
| URL | https://www.nber.org/papers/w22516 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 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/580190 |
| 推荐引用方式 GB/T 7714 | Francis X. Diebold,Minchul Shin. Assessing Point Forecast Accuracy by Stochastic Error Distance. 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 | ||
| w22516.pdf（348KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
