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| Estimation robuste double multi-périodes× | Différence-en-différences (Diff-in-Diff)× | |
|---|---|---|
| Domaine≠ | Inférence causale | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1994-2021 | 1994 |
| Auteur d'origine≠ | Robins, Rotnitzky, and Zhao; extended by Bang & Robins (2005) and Callaway & Sant'Anna (2021) | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| Type≠ | Semiparametric causal estimator | Causal inference / panel regression |
| Source fondatrice≠ | Bang, H., & Robins, J. M. (2005). Doubly robust estimation in missing data and causal inference models. Biometrics, 61(4), 962-973. DOI ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Alias≠ | longitudinal DR estimation, multi-period DR, multi-wave doubly robust, sequential doubly robust estimation | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| Apparentées≠ | 6 | 5 |
| Résumé≠ | Multi-period doubly robust (DR) estimation extends the classic doubly robust approach to longitudinal settings with multiple treatment periods and time points. It combines an outcome regression model and a propensity score model for each period, retaining consistency of the causal effect estimate as long as at least one of the two models is correctly specified at every time point. | 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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