| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP14025 |
| DP14025 When the U.S. catches a cold, Canada sneezes: a lower-bound tale told by deep learning | |
| Vadym Lepetyuk; Serguei Maliar | |
| 发表日期 | 2019-09-25 |
| 出版年 | 2019 |
| 语种 | 英语 |
| 摘要 | The Canadian economy was not initially hit by the 2007-2009 Great Recession but ended up having a prolonged episode of the effective lower bound (ELB) on nominal interest rates. To investigate the Canadian ELB experience, we build a "baby" ToTEM model -- a scaled-down version of the Terms of Trade Economic Model (ToTEM) of the Bank of Canada. Our model includes 49 nonlinear equations and 21 state variables. To solve such a high-dimensional model, we develop a projection deep learning algorithm -- a combination of unsupervised and supervised (deep) machine learning techniques. Our findings are as follows: The Canadian ELB episode was contaminated from abroad via large foreign demand shocks. Prolonged ELB episodes are easy to generate with foreign shocks, unlike with domestic shocks. Nonlinearities associated with the ELB constraint have virtually no impact on the Canadian economy but other nonlinearities do, in particular, the degree of uncertainty and specific closing condition used to induce the model's stationarity. |
| 主题 | Monetary Economics and Fluctuations |
| 关键词 | Central banking Totem Machine learning Deep learning Supervised learning Neural networks Clustering analysis large-scale model New keynesian model Zlb |
| URL | https://cepr.org/publications/dp14025-0 |
| 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/542912 |
| 推荐引用方式 GB/T 7714 | Vadym Lepetyuk,Serguei Maliar. DP14025 When the U.S. catches a cold, Canada sneezes: a lower-bound tale told by deep learning. 2019. |
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