方法对比
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| 政策评估中的熵平衡法× | 双重差分法 (Diff-in-Diff)× | |
|---|---|---|
| 领域≠ | 因果推断 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2012 | 1994 |
| 提出者≠ | Jens Hainmueller | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| 类型≠ | Preprocessing / reweighting estimator | Causal inference / panel regression |
| 开创性文献≠ | Hainmueller, J. (2012). Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies. Political Analysis, 20(1), 25-46. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| 别名≠ | Entropy Balancing, EB Weighting, Maximum-Entropy Reweighting, Hainmueller Balancing | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| 相关≠ | 4 | 5 |
| 摘要≠ | Entropy balancing is a maximum-entropy reweighting method that assigns weights to control-group units so that their weighted covariate moments exactly match those of the treated group. Introduced by Hainmueller (2012), it provides exact balance on specified moments without iterative propensity-score trimming, making it a powerful preprocessing tool for causal policy evaluation in observational studies. | Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes. |
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