Krahasoni metodat
Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.
| Instrumentet e Ndryshueshmërisë së Efektit të Trajtimit (HTE-IV)× | Metoda e Variablave Instrumentalë (IV) për Inferencën Kauzale× | |
|---|---|---|
| Fusha≠ | Inferenca kauzale | Ekonomia shëndetësore |
| Familja≠ | Regression model | Process / pipeline |
| Viti i origjinës≠ | 1994 | 1990s (modern applications) |
| Krijuesi≠ | Imbens & Angrist | Angrist & Pischke (applied econometrics); rooted in econometric theory |
| Lloji≠ | Causal inference / IV with effect heterogeneity | Method |
| Burimi themelues≠ | 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: Princeton University Press. link ↗ |
| Emërtime të tjera | HTE-IV, LATE estimator, IV with effect heterogeneity, local average treatment effect IV | IV, two-stage least squares, TSLS, causal estimation |
| Të lidhura≠ | 4 | 3 |
| Përmbledhja≠ | 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. | Instrumental variables (IV) is an econometric method to estimate causal effects when treatment or exposure is not randomly assigned and confounding is severe or unmeasured. IV relies on a third variable (instrument) that influences treatment but does not directly affect the outcome, allowing researchers to isolate the causal effect from the noise of confounding. Developed extensively in econometrics (Angrist & Pischke, 1990s–2000s), IV methods are increasingly used in health economics and health services research to leverage natural experiments and policy changes. |
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