| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w25532 |
| 来源ID | Working Paper 25532 |
| Synthetic Difference In Differences | |
| Dmitry Arkhangelsky; Susan Athey; David A. Hirshberg; Guido W. Imbens; Stefan Wager | |
| 发表日期 | 2019-02-11 |
| 出版年 | 2019 |
| 语种 | 英语 |
| 摘要 | We present a new estimator for causal effects with panel data that builds on insights behind the widely used difference in differences and synthetic control methods. Relative to these methods we find, both theoretically and empirically, that this "synthetic difference in differences" estimator has desirable robustness properties, and that it performs well in settings where the conventional estimators are commonly used in practice. We study the asymptotic behavior of the estimator when the systematic part of the outcome model includes latent unit factors interacted with latent time factors, and we present conditions for consistency and asymptotic normality. |
| 主题 | Econometrics |
| URL | https://www.nber.org/papers/w25532 |
| 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/583205 |
| 推荐引用方式 GB/T 7714 | Dmitry Arkhangelsky,Susan Athey,David A. Hirshberg,et al. Synthetic Difference In Differences. 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 | ||
| w25532.pdf（645KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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