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| Estimateur par appariement pour l'évaluation des politiques× | Différence-en-différences (Diff-in-Diff)× | |
|---|---|---|
| Domaine≠ | Inférence causale | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1998-2006 | 1994 |
| Auteur d'origine≠ | Heckman, Ichimura & Todd; Abadie & Imbens | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| Type≠ | Non-parametric causal estimator | Causal inference / panel regression |
| Source fondatrice≠ | Abadie, A., & Imbens, G. W. (2006). Large sample properties of matching estimators for average treatment effects. Econometrica, 74(1), 235-267. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Alias≠ | matching estimator, program evaluation matching, treatment effect matching, Abadie-Imbens estimator | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| Apparentées≠ | 6 | 5 |
| Résumé≠ | The policy evaluation matching estimator estimates the causal effect of a program or policy on treated units by pairing each participant with one or more non-participants who share similar pre-treatment characteristics. Developed rigorously by Heckman, Ichimura & Todd (1998) and Abadie & Imbens (2006), it avoids parametric outcome models and is the standard non-parametric tool for program and policy evaluation. | 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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