Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Heterogene Behandeleffect Instrumentele Variabelen (HTE-IV)× | Lokale Gemiddelde Behandelingsuitkomst (LATE / CACE)× | |
|---|---|---|
| Vakgebied | Causale inferentie | Causale inferentie |
| Familie | Regression model | Regression model |
| Jaar van ontstaan | 1994 | 1994 |
| Grondlegger≠ | Imbens & Angrist | Imbens & Angrist (1994); Angrist, Imbens & Rubin (1996) |
| Type≠ | Causal inference / IV with effect heterogeneity | Instrumental-variable causal estimand |
| Oorspronkelijke bron | Imbens, G. W., & Angrist, J. D. (1994). Identification and Estimation of Local Average Treatment Effects. Econometrica, 62(2), 467-475. DOI ↗ | Imbens, G. W., & Angrist, J. D. (1994). Identification and Estimation of Local Average Treatment Effects. Econometrica, 62(2), 467-475. DOI ↗ |
| Aliassen | 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) |
| Verwant≠ | 4 | 5 |
| Samenvatting≠ | 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. |
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