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空间回归不连续设计 (Spatial RDD)×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2010s1994
提出者Popularized by Dell (2010); formalized for geographic boundaries by Keele & Titiunik (2015)Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
类型Quasi-experimental causal inferenceCausal inference / panel regression
开创性文献Dell, M. (2010). The Persistent Effects of Peru's Mining Mita. Econometrica, 78(6), 1863-1903. DOI ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
别名Spatial RDD, Geographic RDD, Border RD Design, Geographic Discontinuity Designdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
相关45
摘要Spatial Regression Discontinuity Design uses a geographic or administrative boundary as the threshold that assigns units to treatment. Observations just inside one side of the boundary are compared with those just outside it, exploiting the near-random variation in treatment status near the cutoff to recover a local causal effect. The approach is widely used in economics, political science, and public health when policies or institutions change sharply at a border.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: Spatial Regression Discontinuity Design · Difference-in-Differences. 于 2026-06-17 检索自 https://scholargate.app/zh/compare