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Dynamisch Event Study Ontwerp×Difference-in-Differences (DiD)×
VakgebiedCausale inferentieEconometrie
FamilieRegression modelRegression model
Jaar van ontstaan2021 (canonical treatment); practice since 1990s)1994
GrondleggerSun & Abraham (2021); Callaway & Sant'Anna (2021) — building on earlier event-study traditions in finance and economicsCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TypeQuasi-experimental / causal inferenceCausal inference / panel regression
Oorspronkelijke bronSun, L., & Abraham, S. (2021). Estimating dynamic treatment effects in event studies with heterogeneous treatment effects. Journal of Econometrics, 225(2), 175-199. DOI ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Aliassendynamic DiD, lead-lag event study, relative-time event study, event-time regressiondiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Verwant35
SamenvattingThe dynamic event study design extends the standard difference-in-differences framework by estimating treatment effects at each period before and after the event, rather than collapsing everything into a single post-treatment coefficient. By plotting lead and lag coefficients against relative event time, researchers can simultaneously test for pre-existing trends and trace how the causal effect evolves over multiple post-treatment periods.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.
ScholarGateGegevensset
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ScholarGateMethoden vergelijken: Dynamic Event Study Design · Difference-in-Differences. Geraadpleegd op 2026-06-15 via https://scholargate.app/nl/compare