Comparar métodos

	Modelo de Painel de Efeitos Fixos	Método de Variáveis Instrumentais (VI) para Inferência Causal
Área	Econometria	Economia da saúde
Família	Regression model	Process / pipeline
Ano de origem	2005	1990s (modern applications)
Autor original	Baltagi (textbook treatment); Hausman test for FE vs RE choice	Angrist & Pischke (applied econometrics); rooted in econometric theory
Tipo	Panel data regression	Method
Fonte seminal	Hausman, J. A. (1978). Specification Tests in Econometrics. Econometrica, 46(6), 1251–1271.	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
Outros nomes	within estimator, panel fixed effects, entity fixed effects model, Panel Sabit Etkiler Modeli	IV, two-stage least squares, TSLS, causal estimation
Relacionados	5	3
Resumo	The fixed effects panel model estimates relationships in panel data (many units observed over time) by exploiting only the within-unit variation, so that unobserved time-invariant heterogeneity is controlled away. It is the central within estimator developed in Baltagi's Econometric Analysis of Panel Data (2005), and the choice between it and the random effects model is settled by the Hausman (1978) test.	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.