| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP10461 |
| DP10461 Fast ML estimation of dynamic bifactor models: an application to European inflation | |
| ENRIQUE SENTANA | |
| 发表日期 | 2015-03-01 |
| 出版年 | 2015 |
| 语种 | 英语 |
| 摘要 | We generalise the spectral EM algorithm for dynamic factor models in Fiorentini, Galesi and Sentana (2014) to bifactor models with pervasive global factors complemented by regional ones. We exploit the sparsity of the loading matrices so that researchers can estimate those models by maximum likelihood with many series from multiple regions. We also derive convenient expressions for the spectral scores and information matrix, which allows us to switch to the scoring algorithm near the optimum. We explore the ability of a model with a global factor and three regional ones to capture inflation dynamics across 25 European countries over 1999-2014. |
| 主题 | International Macroeconomics |
| 关键词 | Euro area Inflation convergence Spectral maximum likelihood Wiener-kolmogorov filter |
| URL | https://cepr.org/publications/dp10461 |
| 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/539293 |
| 推荐引用方式 GB/T 7714 | ENRIQUE SENTANA. DP10461 Fast ML estimation of dynamic bifactor models: an application to European inflation. 2015. |
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