পদ্ধতির তুলনা করুন

	শিক্ষায় ডিফারেন্স-ইন-ডিফারেন্সেস (DiD) গবেষণা	কারণগত অনুমানের জন্য ইনস্ট্রুমেন্টাল ভ্যারিয়েবলস (IV) পদ্ধতি
ক্ষেত্র	কার্যকারণ অনুমান	স্বাস্থ্য অর্থনীতি
পরিবার	Regression model	Process / pipeline
উদ্ভবের বছর	1990s–2000s	1990s (modern applications)
প্রবর্তক	Dynarski, Card, Angrist, and colleagues — applied in education economics from the 1990s onward	Angrist & Pischke (applied econometrics); rooted in econometric theory
ধরন	Quasi-experimental causal inference	Method
মৌলিক উৎস	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.
অপর নাম	DiD in education, education DiD, quasi-experimental education design, education policy DiD	IV, two-stage least squares, TSLS, causal estimation
সম্পর্কিত	5	3
সারসংক্ষেপ	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.