| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP15164 |
| DP15164 Estimating DSGE Models: Recent Advances and Future Challenges | |
| Jesus Fernandez-Villaverde; Pablo A. Guerron-Quintana | |
| 发表日期 | 2020-08-13 |
| 出版年 | 2020 |
| 语种 | 英语 |
| 摘要 | We review the current state of the estimation of DSGE models. After introducing a general framework for dealing with DSGE models, the state-space representation, we discuss how to evaluate moments or the likelihood function implied by such a structure. We discuss, in varying degrees of detail, recent advances in the field, such as the tempered particle filter, approximated Bayesian computation, the Hamiltonian Monte Carlo, variational inference, and machine learning, methods that show much promise, but that have not been fully explored yet by the DSGE community. We conclude by outlining three future challenges for this line of research. |
| 主题 | Monetary Economics and Fluctuations |
| 关键词 | Dsge models Estimation Bayesian methods Mcmc Variational inference |
| URL | https://cepr.org/publications/dp15164 |
| 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/544132 |
| 推荐引用方式 GB/T 7714 | Jesus Fernandez-Villaverde,Pablo A. Guerron-Quintana. DP15164 Estimating DSGE Models: Recent Advances and Future Challenges. 2020. |
| 条目包含的文件 | 条目无相关文件。 | |||||
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
