Võrdle meetodeid
Vaata valitud meetodeid kõrvuti; erinevad read on esile tõstetud.
| Mitte-lineaarne süsteem-GMM× | Instrumentaalmuutujate (IV) meetod kausaalse järelduse tegemiseks× | |
|---|---|---|
| Valdkond≠ | Ökonomeetria | Terviseökonoomika |
| Perekond≠ | Regression model | Process / pipeline |
| Tekkeaasta≠ | 1982 | 1990s (modern applications) |
| Looja≠ | Lars Peter Hansen | Angrist & Pischke (applied econometrics); rooted in econometric theory |
| Tüüp≠ | System estimator | Method |
| Algallikas≠ | Hansen, L. P. (1982). Large sample properties of generalized method of moments estimators. Econometrica, 50(4), 1029–1054. DOI ↗ | Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press. link ↗ |
| Rööpnimetused | NLS-GMM, nonlinear system generalized method of moments, system GMM for nonlinear models, NL-SGMM | IV, two-stage least squares, TSLS, causal estimation |
| Seotud≠ | 4 | 3 |
| Kokkuvõte≠ | Nonlinear System GMM extends the Generalized Method of Moments framework to estimate a system of structural equations in which the parameter vector enters the moment conditions nonlinearly. It jointly exploits moment restrictions across multiple equations, yielding efficiency gains over single-equation approaches when the equations share parameters or have correlated disturbances. | 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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