Linganisha mbinu

	Tofauti-ndani-ya-Tofauti 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	1990s–2000s	1990s (modern applications)
Mwanzilishi	Dynarski, Card, Angrist, and colleagues — applied in education economics from the 1990s onward	Angrist & Pischke (applied econometrics); rooted in econometric theory
Aina	Quasi-experimental causal inference	Method
Chanzo asilia	Dynarski, S. M. (2003). Does Aid Matter? Measuring the Effect of Student Aid on College Attendance and Completion. American Economic Review, 93(1), 279-288.	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
Majina mbadala	DiD in education, education DiD, quasi-experimental education design, education policy DiD	IV, two-stage least squares, TSLS, causal estimation
Zinazohusiana	5	3
Muhtasari	Difference-in-Differences (DiD) in education research applies the classic quasi-experimental DiD estimator to evaluate education policies, programs, and reforms. Researchers compare changes in student, school, or district outcomes between a group exposed to an intervention and a comparable unexposed group across pre- and post-intervention periods, isolating policy effects from background trends.	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.