| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w21564 |
| 来源ID | Working Paper 21564 |
| Low-Frequency Econometrics | |
| Ulrich K. Müller; Mark W. Watson | |
| 发表日期 | 2015-09-21 |
| 出版年 | 2015 |
| 语种 | 英语 |
| 摘要 | Many questions in economics involve long-run or trend variation and covariation in time series. Yet, time series of typical lengths contain only limited information about this long-run variation. This paper suggests that long-run sample information can be isolated using a small number of low-frequency trigonometric weighted averages, which in turn can be used to conduct inference about long-run variability and covariability. Because the low-frequency weighted averages have large sample normal distributions, large sample valid inference can often be conducted using familiar small sample normal inference procedures. Moreover, the general approach is applicable for a wide range of persistent stochastic processes that go beyond the familiar I(0) and I(1) models. |
| 主题 | Econometrics ; Estimation Methods |
| URL | https://www.nber.org/papers/w21564 |
| 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/579239 |
| 推荐引用方式 GB/T 7714 | Ulrich K. Müller,Mark W. Watson. Low-Frequency Econometrics. 2015. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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