Comparer des méthodes

	Variables Instrumentales pour les Effets Hétérogènes du Traitement (HTE-IV)	Effet Traitement Moyen Local (ETML / CACE)
Domaine	Inférence causale	Inférence causale
Famille	Regression model	Regression model
Année d'origine	1994	1994
Auteur d'origine	Imbens & Angrist	Imbens & Angrist (1994); Angrist, Imbens & Rubin (1996)
Type	Causal inference / IV with effect heterogeneity	Instrumental-variable causal estimand
Source fondatrice	Imbens, G. W., & Angrist, J. D. (1994). Identification and Estimation of Local Average Treatment Effects. Econometrica, 62(2), 467-475.	Imbens, G. W., & Angrist, J. D. (1994). Identification and Estimation of Local Average Treatment Effects. Econometrica, 62(2), 467-475.
Alias	HTE-IV, LATE estimator, IV with effect heterogeneity, local average treatment effect IV	LATE, CACE, complier average causal effect, Yerel Ortalama Tedavi Etkisi (LATE / CACE)
Apparentées	4	5
Résumé	Heterogeneous treatment effect IV applies instrumental variables estimation while explicitly acknowledging and modelling that the treatment effect differs across units. Rather than recovering a single average effect, it focuses on the Local Average Treatment Effect (LATE) — the causal effect for compliers, the subpopulation whose treatment status is actually shifted by the instrument — and extends analysis to variation in that effect across observed subgroups.	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.