| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP5289 |
| DP5289 Optimal Delegation | |
| Niko Matouschek; Ricardo Alonso | |
| 发表日期 | 2005-10-23 |
| 出版年 | 2005 |
| 语种 | 英语 |
| 摘要 | This paper explores the usefulness of bagging methods in forecasting economic time series from linear multiple regression models. We focus on the widely studied question of whether the inclusion of indicators of real economic activity lowers the prediction mean-squared error of forecast models of US consumer price inflation. We study bagging methods for linear regression models with correlated regressors and for factor models. We compare the accuracy of simulated out-of-sample forecasts of inflation based on these bagging methods to that of alternative forecast methods, including factor model forecasts, shrinkage estimator forecasts, combination forecasts and Bayesian model averaging. We find that bagging methods in this application are almost as accurate or more accurate than the best alternatives. Our empirical analysis demonstrates that large reductions in the prediction mean squared error are possible relative to existing methods, a result that is also suggested by the asymptotic analysis of some stylized linear multiple regression examples. |
| 主题 | International Macroeconomics |
| 关键词 | Bootstrap aggregation Bayesian model averaging Forecast combination Factor models Shrinkage estimation Forecast model selection Pre-testing |
| URL | https://cepr.org/publications/dp5289 |
| 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/534164 |
| 推荐引用方式 GB/T 7714 | Niko Matouschek,Ricardo Alonso. DP5289 Optimal Delegation. 2005. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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