| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP11560 |
| DP11560 Large Time-Varying Parameter VARs: A Non-Parametric Approach | |
| Massimiliano Marcellino; George Kapetanios; Fabrizio Venditti | |
| 发表日期 | 2016-10-06 |
| 出版年 | 2016 |
| 语种 | 英语 |
| 摘要 | In this paper we introduce a nonparametric estimation method for a large Vector Autoregression (VAR) with time-varying parameters. The estimators and their asymptotic distributions are available in closed form. This makes the method computationally efficient and capable of handling information sets as large as those typically handled by factor models and Factor Augmented VARs (FAVAR). When applied to the problem of forecasting key macroeconomic variables, the method outperforms constant parameter benchmarks and large (parametric) Bayesian VARs with time-varying parameters. The tool can also be used for structural analysis. As an example, we study the time-varying effects of oil price innovations on sectoral U.S. industrial output. We find that the changing interaction between unexpected oil price increases and business cycle fluctuations is shaped by the durable materials sector, rather by the automotive sector on which a large part of the literature has typically focused. |
| 主题 | Monetary Economics and Fluctuations |
| URL | https://cepr.org/publications/dp11560 |
| 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/540374 |
| 推荐引用方式 GB/T 7714 | Massimiliano Marcellino,George Kapetanios,Fabrizio Venditti. DP11560 Large Time-Varying Parameter VARs: A Non-Parametric Approach. 2016. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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