| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP13245 |
| DP13245 A composite likelihood approach for dynamic structural models | |
| Fabio Canova; Christian Matthes | |
| 发表日期 | 2018-10-15 |
| 出版年 | 2018 |
| 语种 | 英语 |
| 摘要 | We describe how to use the composite likelihood to ameliorate estimation, computational, and inferential problems in dynamic stochastic general equilibrium models. We present a number of situations where the methodology has the potential to resolve well-known problems and formally justifies existing practices. In each case we consider, we provide an example to illustrate how the approach works and its properties in practice. |
| 主题 | International Macroeconomics and Finance ; Monetary Economics and Fluctuations |
| 关键词 | Dynamic structural models Composite likelihood Identification Singularity Large scale models Panel data |
| URL | https://cepr.org/publications/dp13245 |
| 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/542053 |
| 推荐引用方式 GB/T 7714 | Fabio Canova,Christian Matthes. DP13245 A composite likelihood approach for dynamic structural models. 2018. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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