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反事实影响评估 (CIE)×双重差分法 (Diff-in-Diff)×
领域因果推断计量经济学
方法族Regression modelRegression model
起源年份1970s–2000s1994
提出者Heckman, Imbens, Rubin, and the program evaluation literatureCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
类型Causal inference / program evaluationCausal inference / panel regression
开创性文献Heckman, J. J., & Vytlacil, E. J. (2007). Econometric evaluation of social programs, Part I: Causal models, structural models and econometric policy evaluation. Handbook of Econometrics, 6B, 4779-4874. DOI ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
别名CIE, counterfactual evaluation, counterfactual policy evaluation, impact evaluationdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
相关55
摘要Counterfactual Impact Evaluation is a family of causal methods that estimates the effect of an intervention by comparing what actually happened to participants with what would have happened had the intervention not taken place. Formalised in the Rubin Causal Model and extended by Heckman, Imbens and others, CIE underlies most modern program and policy evaluation practice.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.
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ScholarGate方法对比: Counterfactual Impact Evaluation · Difference-in-Differences. 于 2026-06-17 检索自 https://scholargate.app/zh/compare