| 来源类型 | Discussion paper
|
| 规范类型 | 论文
|
| 来源ID | DP13034
|
| DP13034 The Forcasting Performance of Dynamic Factor Models with Vintage Data |
| Mario Forni
|
| 发表日期 | 2018-07-03
|
| 出版年 | 2018
|
| 语种 | 英语
|
| 摘要 | We present a comparative analysis of the forecasting performance of two dynamic factor models, the Stock and Watson (2002a, b) model and the Forni, Hallin, Lippi and Reichlin (2005) model, based on vintage data. Our dataset contains 107 monthly US “first release” macroeconomic and financial vintage time series, spanning the 1996:12 to 2017:6 period with monthly periodicity, extracted from the Bloomberg database†. We compute real-time one-month-ahead forecasts with both models for four key macroeconomic variables: the month-on-month change in industrial production, the unemployment rate, the core consumer price index and the ISM Purchasing Managers’ Index. First, we find that both the Stock and Watson and the Forni, Hallin, Lippi and Reichlin models outperform simple autoregressions for industrial production, unemployment rate and consumer prices, but that only the first model does so for the PMI. Second, we find that neither models always outperform the other. While Forni, Hallin, Lippi and Reichlin’s beats Stock and Watson’s in forecasting industrial production and consumer prices, the opposite happens for the unemployment rate and the PMI. |
| 主题 | Monetary Economics and Fluctuations
|
| 关键词 | Dynamic factor models
Forecasting
Forecasting performance
Vintage data
First release data
|
| URL | https://cepr.org/publications/dp13034
|
| 来源智库 | Centre for Economic Policy Research (United Kingdom)
|
| 资源类型 | 智库出版物
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| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/541841
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推荐引用方式
GB/T 7714 |
Mario Forni. DP13034 The Forcasting Performance of Dynamic Factor Models with Vintage Data. 2018.
|
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