Salīdzināt metodes

	Furjē-Hausmana tests	Instrumentālo mainīgo (IV) metode cēloņsakarību noteikšanai
Nozare	Ekonometrija	Veselības ekonomika
Saime	Regression model	Process / pipeline
Izcelsmes gads	2000s–2010s	1990s (modern applications)
Autors	Extends Hausman (1978) using Gallant's (1981) Fourier flexible functional form; applied in panel/time-series settings by Christopoulos & Leon-Ledesma (2004) and subsequent literature	Angrist & Pischke (applied econometrics); rooted in econometric theory
Tips	Specification / endogeneity test	Method
Pirmavots	Christopoulos, D. K., & Leon-Ledesma, M. A. (2004). Current account sustainability in the US: What do we really know about it? Journal of International Money and Finance, 23(5), 821–840.	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
Citi nosaukumi	Fourier-Hausman endogeneity test, Fourier augmented Hausman test, nonlinear Hausman test, flexible Hausman specification test	IV, two-stage least squares, TSLS, causal estimation
Saistītās	5	3
Kopsavilkums	The Fourier Hausman test extends the classical Hausman endogeneity test by augmenting the regression with Fourier trigonometric terms — sines and cosines of time — so that the test remains valid even when the data-generating process contains smooth structural breaks or gradual nonlinearities that conventional linear specifications miss.	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.