Linganisha mbinu

	Tathmini ya Athari ya Kinyume katika Utafiti wa Elimu	Tofauti-katika-Tofauti (Diff-in-Diff)
Nyanja	Uhitimisho wa Kisababishi	Ekonometriki
Familia	Regression model	Regression model
Mwaka wa asili	2000s–2010s	1994
Mwanzilishi	Blundell & Costa Dias; formalized for EU education policy by the European Commission Joint Research Centre	Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
Aina	Quasi-experimental causal inference framework	Causal inference / panel regression
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 University Press. ISBN: 978-0691120355
Majina mbadala	CIE in education, counterfactual program evaluation, causal impact evaluation, education policy impact evaluation	diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Zinazohusiana	5	5
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.	Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes.