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合成控制法用于政策评估×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2003-20101994
提出者Alberto Abadie & Javier Gardeazabal; extended by Abadie, Diamond & HainmuellerCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
类型Causal inference / comparative case studyCausal inference / panel regression
开创性文献Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program. Journal of the American Statistical Association, 105(490), 493-505. DOI ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
别名Synthetic Control Method, SCM, Synthetic Control, Abadie-Diamond-Hainmueller methoddiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
相关55
摘要The Synthetic Control Method (SCM) is a causal inference technique for evaluating the effect of a policy or intervention on a single treated unit — such as a region, country, or firm — by constructing a weighted combination of untreated comparison units that closely mirrors the treated unit before the intervention. Introduced by Abadie and Gardeazabal (2003) and formalized by Abadie, Diamond, and Hainmueller (2010), it provides a data-driven, transparent counterfactual for comparative case studies.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: Policy Evaluation Synthetic Control Method · Difference-in-Differences. 于 2026-06-17 检索自 https://scholargate.app/zh/compare