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| 패널 데이터 엔트로피 균형× | 엔트로피 균형× | |
|---|---|---|
| 분야 | 인과추론 | 인과추론 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 2012 (cross-section); panel adaptation mid-2010s onward | 2012 |
| 창시자≠ | Hainmueller (2012); extended to panel settings by subsequent applied econometric work | Jens Hainmueller |
| 유형≠ | Covariate balancing / reweighting estimator | Covariate-balancing reweighting |
| 원전 | 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 ↗ | 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 ↗ |
| 별칭 | EB-panel, panel entropy balancing, entropy reweighting in panel data, panel-EB | EB, entropy reweighting, covariate balancing via entropy, Hainmueller balancing |
| 관련≠ | 5 | 6 |
| 요약≠ | Panel data entropy balancing extends Hainmueller's (2012) entropy balancing method to longitudinal settings. It computes unit-level weights for control observations so that their covariate moments exactly match those of the treatment group across panel periods, then plugs these weights into a weighted panel regression to estimate causal treatment effects without requiring a correctly specified propensity score model. | Entropy balancing is a preprocessing method for causal inference that assigns weights to control-group units so that the reweighted control sample matches the treatment group exactly on a chosen set of covariate moments (means, variances, skewness). Introduced by Hainmueller (2012), it replaces trial-and-error propensity-score trimming with a constrained maximum-entropy optimisation that achieves balance in a single step. |
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