| 来源类型 | Discussion paper
|
| 规范类型 | 论文
|
| 来源ID | DP10168
|
| DP10168 Window Selection for Out-of-Sample Forecasting with Time-Varying Parameters |
| Barbara Rossi; Atsushi Inoue
|
| 发表日期 | 2014-09-28
|
| 出版年 | 2014
|
| 语种 | 英语
|
| 摘要 | While forecasting is a common practice in academia, government and business alike, practitioners are often left wondering how to choose the sample for estimating forecasting models. When we forecast inflation in 2014, for example, should we use the last 30 years of data or the last 10 years of data? There is strong evidence of structural changes in economic time series, and the forecasting performance is often quite sensitive to the choice of such window size. In this paper, we develop a novel method for selecting the estimation window size for forecasting. Specifically, we propose to choose the optimal window size that minimizes the forecaster's quadratic loss function, and we prove the asymptotic validity of our approach. Our Monte Carlo experiments show that our method performs quite well under various types of structural changes. When applied to forecasting US real output growth and inflation, the proposed method tends to improve upon conventional methods. |
| 主题 | International Macroeconomics
|
| 关键词 | Forecasting
Gdp growth
inflation
Instabilities
Structural change
|
| URL | https://cepr.org/publications/dp10168
|
| 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/539001
|
推荐引用方式
GB/T 7714 |
Barbara Rossi,Atsushi Inoue. DP10168 Window Selection for Out-of-Sample Forecasting with Time-Varying Parameters. 2014.
|
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