Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Effet Traitement Moyen Local (ETML / CACE)× | Variables instrumentales par moindres carrés en deux étapes (VI/2SLS)× | |
|---|---|---|
| Domaine | Inférence causale | Inférence causale |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1994 | 2009 |
| Auteur d'origine≠ | Imbens & Angrist (1994); Angrist, Imbens & Rubin (1996) | Angrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory) |
| Type≠ | Instrumental-variable causal estimand | Instrumental-variables regression |
| Source fondatrice≠ | Imbens, G. W., & Angrist, J. D. (1994). Identification and Estimation of Local Average Treatment Effects. Econometrica, 62(2), 467-475. DOI ↗ | Angrist, J. D. & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Alias≠ | LATE, CACE, complier average causal effect, Yerel Ortalama Tedavi Etkisi (LATE / CACE) | instrumental variables, IV estimation, 2SLS, instrumental variable regression |
| Apparentées | 5 | 5 |
| Résumé≠ | The Local Average Treatment Effect is an instrumental-variable estimand, introduced by Imbens and Angrist (1994) and formalised with Rubin (1996), that recovers the average treatment effect for the subpopulation of compliers — units whose treatment status is actually moved by the instrument. It is closely tied to compliance analysis. | IV/2SLS is a two-stage estimation method that recovers the causal effect of an endogenous regressor by isolating the part of its variation driven by an external instrument. It is the workhorse identification strategy in modern applied econometrics, developed at length in Angrist and Pischke's Mostly Harmless Econometrics (2009). |
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