Linganisha mbinu

	Tathmini ya Athari ya Kinyume katika Utafiti wa Elimu	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	2000s–2010s	1990s (modern applications)
Mwanzilishi	Blundell & Costa Dias; formalized for EU education policy by the European Commission Joint Research Centre	Angrist & Pischke (applied econometrics); rooted in econometric theory
Aina	Quasi-experimental causal inference framework	Method
Chanzo asilia	Blundell, R., & Costa Dias, M. (2002). Alternative approaches to evaluation in empirical microeconomics. Portuguese Economic Journal, 1(2), 91-115.	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
Majina mbadala	CIE in education, counterfactual program evaluation, causal impact evaluation, education policy impact evaluation	IV, two-stage least squares, TSLS, causal estimation
Zinazohusiana	5	3
Muhtasari	Counterfactual impact evaluation (CIE) is the systematic application of causal inference designs — such as difference-in-differences, regression discontinuity, matching, and instrumental variables — to measure the genuine effect of education programs, policies, or interventions by constructing a credible counterfactual: what would have happened to participants had they not been treated.	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.