Сравнение методов

	Regression discontinuity design in education research	Разность разностей (Difference-in-Differences, DiD)
Область	Причинно-следственный вывод	Эконометрика
Семейство	Regression model	Regression model
Год появления	1960 (origination); 1999-2010 (education economics canon)	1994
Автор метода	Thistlethwaite & Campbell (1960); popularized in education economics by Angrist & Lavy (1999), Lee & Lemieux (2010)	Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
Тип	Quasi-experimental causal inference	Causal inference / panel regression
Основополагающий источник	Lee, D. S., & Lemieux, T. (2010). Regression discontinuity designs in economics. Journal of Economic Literature, 48(2), 281-355.	Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Другие названия	RDD in education, education RD design, sharp RDD education, score-cutoff design	diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Связанные	5	5
Сводка	Regression discontinuity design (RDD) in education research exploits a score-based eligibility cutoff — such as a test score threshold, GPA requirement, or age cutoff — to estimate the causal effect of a program, intervention, or policy on student or school outcomes. Units just below and just above the cutoff are treated as near-randomly assigned, enabling credible causal inference without a randomized trial.	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.