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领域因果推断因果推断
方法族Regression modelRegression model
起源年份1960 (original RDD); panel extension codified 2000s–2010s2000s–2010s
提出者Thistlethwaite & Campbell (1960); panel extension developed through Lee & Lemieux (2010) and related applied workShadish, Cook & Campbell (design framework); Bernal, Cummins & Gasparrini (epidemiological tutorial)
类型Causal inference / quasi-experimentalQuasi-experimental causal inference
开创性文献Lee, D. S., & Lemieux, T. (2010). Regression Discontinuity Designs in Economics. Journal of Economic Literature, 48(2), 281-355. DOI ↗Lopez Bernal, J., Cummins, S., & Gasparrini, A. (2017). Interrupted time series regression for the evaluation of public health interventions: a tutorial. International Journal of Epidemiology, 46(1), 348-355. DOI ↗
别名Panel RD, Panel RDD, Longitudinal Regression Discontinuity, Fixed-Effects RDDpanel ITS, multi-unit ITS, panel ITSA, controlled interrupted time series
相关55
摘要Panel data regression discontinuity design (Panel RDD) combines the sharp local identification of a regression discontinuity with the within-unit variation available in repeated-observation panel data. Units are observed across multiple periods, and treatment is assigned based on whether a running variable crosses a known threshold. By leveraging both the discontinuity and panel structure, researchers can control for unobserved unit-level heterogeneity while estimating a causal treatment effect near the threshold.Panel Data Interrupted Time Series (panel ITS) is a quasi-experimental method that estimates the causal effect of an intervention using repeated observations from multiple units over time. By exploiting variation across both units and time periods, it provides stronger causal identification than single-unit ITS, detecting changes in the level and slope of the outcome trajectory immediately following a clearly dated intervention.
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ScholarGate方法对比: Panel Data Regression Discontinuity Design · Panel Data Interrupted Time Series. 于 2026-06-18 检索自 https://scholargate.app/zh/compare