Methoden vergelijken

	Robuuste Difference-in-Differences	Heterogeneous Treatment Effect Difference-in-Differences (HTE-DiD)
Vakgebied	Causale inferentie	Causale inferentie
Familie	Regression model	Regression model
Jaar van ontstaan	2021-2023	2021
Grondlegger	Callaway & Sant'Anna; Sun & Abraham; Roth et al. (synthesised 2021-2023)	Callaway & Sant'Anna; Sun & Abraham
Type	Causal inference / panel regression	Causal inference / panel regression
Oorspronkelijke bron	Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-differences with multiple time periods. Journal of Econometrics, 225(2), 200-230.	Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-Differences with multiple time periods. Journal of Econometrics, 225(2), 200-230.
Aliassen	robust DiD, heterogeneity-robust DiD, staggered DiD, disaggregated ATT DiD	HTE-DiD, heterogeneous DiD, CATT estimator, group-time ATT
Verwant	5	4
Samenvatting	Robust Difference-in-Differences is a family of modern DiD estimators designed to remain valid when treatment timing is staggered across units and treatment effects are heterogeneous over time or across groups. Classical two-way fixed-effects (TWFE) DiD can be severely biased in such settings; robust variants estimate group-time average treatment effects (ATTs) separately and then aggregate them in a theoretically sound way.	HTE-DiD extends the classic Difference-in-Differences estimator to settings where treatment effects vary across units, time periods, or treatment cohorts. Developed formally by Callaway and Sant'Anna (2021) and Sun and Abraham (2021), it avoids the biases that arise when a conventional two-way fixed-effects regression is used with staggered adoption or effect heterogeneity, by estimating cohort-and-time-specific average treatment effects that can then be aggregated flexibly.