| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w28445 |
| 来源ID | Working Paper 28445 |
| Unemployment in the Time of COVID-19: A Flow-Based Approach to Real-time Unemployment Projections | |
| Ayşegül Şahin; Murat Tasci; Jin Yan | |
| 发表日期 | 2021-02-08 |
| 出版年 | 2021 |
| 语种 | 英语 |
| 摘要 | This paper presents a flow-based methodology for real-time unemployment rate projections and shows that this approach performed considerably better at the onset of the COVID-19 recession in the spring 2020 in predicting the peak unemployment rate as well as its rapid decline over the year. It presents an alternative scenario analysis for 2021 based on this methodology and argues that the unemployment rate is likely to decline to 5.4 percent by the end of 2021. The predictive power of the methodology comes from its combined use of real-time data with the flow approach. |
| 主题 | Macroeconomics ; Consumption and Investment ; Business Cycles ; Labor Economics ; Unemployment and Immigration ; COVID-19 |
| URL | https://www.nber.org/papers/w28445 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/586118 |
| 推荐引用方式 GB/T 7714 | Ayşegül Şahin,Murat Tasci,Jin Yan. Unemployment in the Time of COVID-19: A Flow-Based Approach to Real-time Unemployment Projections. 2021. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w28445.pdf（468KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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