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教育研究中的双重差分法×因果推断的工具变量(IV)方法×
领域因果推断卫生经济学
方法族Regression modelProcess / pipeline
起源年份1990s–2000s1990s (modern applications)
提出者Dynarski, Card, Angrist, and colleagues — applied in education economics from the 1990s onwardAngrist & Pischke (applied econometrics); rooted in econometric theory
类型Quasi-experimental causal inferenceMethod
开创性文献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. DOI ↗Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press. link ↗
别名DiD in education, education DiD, quasi-experimental education design, education policy DiDIV, two-stage least squares, TSLS, causal estimation
相关53
摘要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.
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ScholarGate方法对比: Difference-in-Differences in Education Research · Instrumental Variables in Health Research. 于 2026-06-19 检索自 https://scholargate.app/zh/compare