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Регрессионный разрывный дизайн (RDD)×Разность разностей (Difference-in-Differences, DiD)×Модель с фиксированными эффектами для панельных данных×
ОбластьЭконометрикаЭконометрикаЭконометрика
СемействоRegression modelRegression modelRegression model
Год появления200819942014
Автор методаImbens & Lemieux; Lee & Lemieux (modern practice); Cattaneo, Idrobo & TitiunikCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)Hsiao (textbook treatment); within transformation of panel data
ТипQuasi-experimental causal designCausal inference / panel regressionPanel data regression
Основополагающий источникImbens, G. W., & Lemieux, T. (2008). Regression Discontinuity Designs: A Guide to Practice. Journal of Econometrics, 142(2), 615-635. DOI ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗
Другие названияRDD, regression discontinuity, sharp regression discontinuity, Regresyon Süreksizliği Tasarımı (RDD)diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli
Связанные555
СводкаRegression Discontinuity Design is a quasi-experimental method that estimates a local causal effect around a threshold (cutoff) value, comparing units just below and just above the cutoff as if they were almost randomly assigned. It is the design developed for applied practice by Imbens and Lemieux (2008) and by Lee and Lemieux (2010).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.The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014).
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ScholarGateСравнение методов: Regression Discontinuity Design · Difference-in-Differences · Panel Fixed Effects. Получено 2026-06-18 из https://scholargate.app/ru/compare