方法对比
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| 多期粗糙化精确匹配× | 面板数据粗化精确匹配× | |
|---|---|---|
| 领域 | 因果推断 | 因果推断 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2012–2021 | 2012 (CEM); 2021 (panel extension) |
| 提出者≠ | Iacus, King & Porro (CEM, 2012); extended to multi-period panel settings | Iacus, King & Porro (CEM, 2012); panel extension via Imai, Kim & Wang (2021) |
| 类型≠ | Non-parametric matching / causal inference | Matching / quasi-experimental |
| 开创性文献 | Iacus, S. M., King, G., & Porro, G. (2012). Causal inference without balance checking: Coarsened exact matching. Political Analysis, 20(1), 1-24. DOI ↗ | Iacus, S. M., King, G., & Porro, G. (2012). Causal Inference without Balance Checking: Coarsened Exact Matching. Political Analysis, 20(1), 1-24. DOI ↗ |
| 别名≠ | Multi-period CEM, Longitudinal CEM, Panel CEM, Multi-wave CEM | Panel CEM, CEM for panel data, coarsened exact matching with panel data |
| 相关 | 6 | 6 |
| 摘要≠ | Multi-period Coarsened Exact Matching (multi-period CEM) extends the CEM framework of Iacus, King, and Porro to longitudinal data with multiple pre- and post-treatment periods. It bins continuous covariates into coarsened categories, matches treated and control units that fall into the same cells across all relevant time periods, and then estimates a weighted average treatment effect that accounts for temporal structure. | Panel Data Coarsened Exact Matching applies the Coarsened Exact Matching (CEM) algorithm to repeated-measures panel data, matching treated and control units within the same coarsened covariate strata across multiple time periods. It balances pre-treatment characteristics before estimating a causal treatment effect, combining the transparency of exact matching with the richer identification available in longitudinal datasets. |
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