Salīdzināt metodes

	Paneļa modelis ar fiksētajiem efektiem	Instrumentālo mainīgo (IV) metode cēloņsakarību noteikšanai
Nozare	Ekonometrija	Veselības ekonomika
Saime	Regression model	Process / pipeline
Izcelsmes gads	2005	1990s (modern applications)
Autors	Baltagi (textbook treatment); Hausman test for FE vs RE choice	Angrist & Pischke (applied econometrics); rooted in econometric theory
Tips	Panel data regression	Method
Pirmavots	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.
Citi nosaukumi	within estimator, panel fixed effects, entity fixed effects model, Panel Sabit Etkiler Modeli	IV, two-stage least squares, TSLS, causal estimation
Saistītās	5	3
Kopsavilkums	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.