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Dizajn udalostnej štúdie (kauzálna udalostná štúdia)×Regresný diskontinuitný dizajn (RDD)×
OdborKauzálna inferenciaKauzálna inferencia
RodinaRegression modelRegression model
Rok vzniku20212008
TvorcaSun & Abraham (2021); Callaway & Sant'Anna (2021)Imbens & Lemieux (guide to practice); Cattaneo, Idrobo & Titiunik (practical introduction)
TypDynamic causal panel regressionQuasi-experimental causal design
Pôvodný zdrojSun, L. & Abraham, S. (2021). Estimating Dynamic Treatment Effects in Event Studies with Heterogeneous Treatment Effects. Journal of Econometrics, 225(2), 175–199. DOI ↗Imbens, G. W., & Lemieux, T. (2008). Regression Discontinuity Designs: A Guide to Practice. Journal of Econometrics, 142(2), 615-635. DOI ↗
Ďalšie názvydynamic difference-in-differences, event-study DiD, dynamic treatment effects, leads-and-lags modelRDD, regression discontinuity design, sharp RDD, fuzzy RDD
Príbuzné55
ZhrnutieThe event study design is a generalised difference-in-differences model that estimates a separate treatment-effect coefficient for each period before and after an intervention, tracing the dynamics of the effect over event time. Its modern, heterogeneity-robust form was developed by Sun & Abraham (2021) and Callaway & Sant'Anna (2021).Regression Discontinuity Design is a quasi-experimental method that identifies a causal effect by locally comparing units just above and just below a cutoff on a continuous assignment (running) variable. Formalised for applied work by Imbens and Lemieux (2008) and developed as a practical framework by Cattaneo, Idrobo, and Titiunik (2020), it estimates a local average treatment effect (LATE) at the threshold.
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ScholarGatePorovnať metódy: Event Study Design · Regression Discontinuity. Získané 2026-06-18 z https://scholargate.app/sk/compare