| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP10417 |
| DP10417 A spectral EM algorithm for dynamic factor models | |
| ENRIQUE SENTANA | |
| 发表日期 | 2015-02-15 |
| 出版年 | 2015 |
| 语种 | 英语 |
| 摘要 | We introduce a frequency domain version of the EM algorithm for general dynamic factor models. We consider both AR and ARMA processes, for which we develop iterative indirect inference procedures analogous to the algorithms in Hannan (1969). Although our proposed procedure allows researchers to estimate such models by maximum likelihood with many series even without good initial values, we recommend switching to a gradient method that uses the EM principle to swiftly compute frequency domain analytical scores near the optimum. We successfully employ our algorithm to construct an index that captures the common movements of US sectoral employment growth rates. |
| 主题 | International Macroeconomics |
| 关键词 | indirect inference Kalman filter Sectoral employment Spectral maximum likelihood Wiener-kolmogorov filter |
| URL | https://cepr.org/publications/dp10417 |
| 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/539249 |
| 推荐引用方式 GB/T 7714 | ENRIQUE SENTANA. DP10417 A spectral EM algorithm for dynamic factor models. 2015. |
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