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Policy Evaluation Event Study Design×Paneldatamodell med faste effekter×
FagfeltKausal inferensØkonometri
FamilieRegression modelRegression model
Opprinnelsesår1993-20212014
OpphavspersonAndrews (1993), MacKinlay (1997); formalized for policy evaluation by Freyaldenhoven, Hansen & Shapiro (2019) and Callaway & Sant'Anna (2021)Hsiao (textbook treatment); within transformation of panel data
TypeQuasi-experimental / causal inferencePanel data regression
Opprinnelig kildeCallaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-differences with multiple time periods. Journal of Econometrics, 225(2), 200-230. DOI ↗Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗
Aliasevent study, event-study DiD, dynamic DiD, PEESDfixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli
Relaterte55
SammendragA policy evaluation event study design is a quasi-experimental approach that estimates causal effects of a policy by plotting treatment-period-by-period coefficients around a common event time. It extends difference-in-differences to visualize both pre-treatment parallel trends and the dynamic post-treatment evolution of the policy effect, and has become the standard credibility check in applied policy research.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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ScholarGateSammenlign metoder: Policy Evaluation Event Study Design · Panel Fixed Effects. Hentet 2026-06-17 fra https://scholargate.app/no/compare