| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP14790 |
| DP14790 Panel Forecasts of Country-Level Covid-19 Infectionsliu | |
| Laura Liu; Hyungsik Roger Moon; Frank Schorfheide | |
| 发表日期 | 2020-05-20 |
| 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 | Macroeconomics and Growth |
| 关键词 | Bayesian inference Covid-19 Density forecasts Interval forecasts Panel data models Random effects Sir model |
| URL | https://cepr.org/publications/dp14790 |
| 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/543720 |
| 推荐引用方式 GB/T 7714 | Laura Liu,Hyungsik Roger Moon,Frank Schorfheide. DP14790 Panel Forecasts of Country-Level Covid-19 Infectionsliu. 2020. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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