Linganisha mbinu

	Mtihani wa Mahali pa Kutathmini Sera	Njia ya Vigezo vya Ala (IV) kwa Utafutaji wa Kifungo
Nyanja	Uhitimisho wa Kisababishi	Uchumi wa Afya
Familia	Regression model	Process / pipeline
Mwaka wa asili	1990s–2000s	1990s (modern applications)
Mwanzilishi	Bertrand, Duflo & Mullainathan (2004 canonical formalization); Imbens & Wooldridge (2009 textbook treatment)	Angrist & Pischke (applied econometrics); rooted in econometric theory
Aina	Falsification / specification check	Method
Chanzo asilia	Imbens, G. W., & Wooldridge, J. M. (2009). Recent Developments in the Econometrics of Program Evaluation. Journal of Economic Literature, 47(1), 5-86.	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
Majina mbadala	placebo test, falsification test, fake treatment test, placebo regression	IV, two-stage least squares, TSLS, causal estimation
Zinazohusiana	4	3
Muhtasari	A policy evaluation placebo test is a falsification check used in quasi-experimental research to validate a causal identification strategy. The researcher applies the same estimation method to a pseudo-treatment — a time period, group, or outcome where the real policy could not have had an effect — and checks that no spurious effect is detected. A null placebo result builds confidence that the main estimate reflects a genuine causal impact rather than bias or confounding.	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.