Compara mètodes

	Diferències de diferències amb efectes de tractament heterogenis (HTE-DiD)	Mètode del Control Sintètic (SCM)
Camp	Inferència causal	Inferència causal
Família	Regression model	Regression model
Any d'origen	2021	2003–2010
Autor original	Callaway & Sant'Anna; Sun & Abraham	Alberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010)
Tipus	Causal inference / panel regression	Quasi-experimental causal inference
Font seminal	Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-Differences with multiple time periods. Journal of Econometrics, 225(2), 200-230.	Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program. Journal of the American Statistical Association, 105(490), 493-505.
Àlies	HTE-DiD, heterogeneous DiD, CATT estimator, group-time ATT	SCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method
Relacionats	4	4
Resum	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.	The Synthetic Control Method estimates the causal effect of a treatment or policy on a single treated unit by constructing a weighted combination of untreated units — the synthetic control — that closely resembles the treated unit before the intervention. The gap between the treated unit and its synthetic counterpart after the intervention is the estimated treatment effect.