Comparer des méthodes

	Modèle à effets fixes pour données de panel	Méthode des variables instrumentales (VI) pour l'inférence causale
Domaine	Économétrie	Économie de la santé
Famille	Regression model	Process / pipeline
Année d'origine	2014	1990s (modern applications)
Auteur d'origine	Hsiao (textbook treatment); within transformation of panel data	Angrist & Pischke (applied econometrics); rooted in econometric theory
Type	Panel data regression	Method
Source fondatrice	Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press.	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
Alias	fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli	IV, two-stage least squares, TSLS, causal estimation
Apparentées	5	3
Résumé	The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014).	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.