| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w25675 |
| 来源ID | Working Paper 25675 |
| Ensemble Methods for Causal Effects in Panel Data Settings | |
| Susan Athey; Mohsen Bayati; Guido Imbens; Zhaonan Qu | |
| 发表日期 | 2019-03-25 |
| 出版年 | 2019 |
| 语种 | 英语 |
| 摘要 | In many prediction problems researchers have found that combinations of prediction methods (“ensembles”) perform better than individual methods. A simple example is random forests, which combines predictions from many regression trees. A striking, and substantially more complex, example is the Netflix Prize competition where the winning entry combined predictions using a wide variety of conceptually very different models. In macro-economic forecasting researchers have often found that averaging predictions from different models leads to more accurate forecasts. In this paper we apply these ideas to synthetic control type problems in panel data setting. In this setting a number of conceptually quite different methods have been developed, with some assuming correlations between units that are stable over time, others assuming stable time series patterns common to all units, and others using factor models. With data on state level GDP for 270 quarters, we focus on three basic approaches to predicting missing values, one from each of these strands of the literature. Rather than try to test the different models against each other and find a true model, we focus on combining predictions based on each of the separate models using ensemble methods. For the ensemble predictor we focus on a weighted average of the three individual methods, with non-negative weights determined through out-of-sample cross-validation. |
| 主题 | Econometrics ; Estimation Methods |
| URL | https://www.nber.org/papers/w25675 |
| 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/583348 |
| 推荐引用方式 GB/T 7714 | Susan Athey,Mohsen Bayati,Guido Imbens,et al. Ensemble Methods for Causal Effects in Panel Data Settings. 2019. |
| 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 | ||
| w25675.pdf（126KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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