| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP10239 |
| DP10239 How good are out of sample forecasting Tests on DSGE models? | |
| Patrick Minford | |
| 发表日期 | 2014-11-09 |
| 出版年 | 2014 |
| 语种 | 英语 |
| 摘要 | Out-of-sample forecasting tests of DSGE models against time-series benchmarks such as an unrestricted VAR are increasingly used to check a) the specification b) the forecasting capacity of these models. We carry out a Monte Carlo experiment on a widely-used DSGE model to investigate the power of these tests. We find that in specification testing they have weak power relative to an in-sample indirect inference test; this implies that a DSGE model may be badly mis-specified and still improve forecasts from an unrestricted VAR. In testing forecasting capacity they also have quite weak power, particularly on the lefthand tail. By contrast a model that passes an indirect inference test of specification will almost definitely also improve on VAR forecasts. |
| 主题 | International Macroeconomics |
| 关键词 | Dsge Forecast performance indirect inference Out of sample forecasts Specification tests Var |
| URL | https://cepr.org/publications/dp10239 |
| 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/539072 |
| 推荐引用方式 GB/T 7714 | Patrick Minford. DP10239 How good are out of sample forecasting Tests on DSGE models?. 2014. |
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