| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w27248 |
| 来源ID | Working Paper 27248 |
| Panel Forecasts of Country-Level Covid-19 Infections | |
| Laura Liu; Hyungsik Roger Moon; Frank Schorfheide | |
| 发表日期 | 2020-05-25 |
| 出版年 | 2020 |
| 语种 | 英语 |
| 摘要 | We use dynamic panel data models to generate density forecasts for daily Covid-19 infections for a panel of countries/regions. At the core of our model is a specification that assumes that the growth rate of active infections can be represented by autoregressive fluctuations around a downward sloping deterministic trend function with a break. Our fully Bayesian approach allows us to flexibly estimate the cross-sectional distribution of heterogeneous coefficients and then implicitly use this distribution as prior to construct Bayes forecasts for the individual time series. According to our model, there is a lot of uncertainty about the evolution of infection rates, due to parameter uncertainty and the realization of future shocks. We find that over a one-week horizon the empirical coverage frequency of our interval forecasts is close to the nominal credible level. Weekly forecasts from our model are published at https://laurayuliu.com/covid19-panel-forecast/. |
| 主题 | Econometrics ; Estimation Methods ; COVID-19 |
| URL | https://www.nber.org/papers/w27248 |
| 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/584920 |
| 推荐引用方式 GB/T 7714 | Laura Liu,Hyungsik Roger Moon,Frank Schorfheide. Panel Forecasts of Country-Level Covid-19 Infections. 2020. |
| 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 | ||
| w27248.pdf（1333KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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。
