Methoden vergleichen

	Die Multi-Period Synthetic Control Method	Differenz-in-Differenzen (DiD)
Fachgebiet	Kausale Inferenz	Ökonometrie
Familie	Regression model	Regression model
Entstehungsjahr	2010-2021	1994
Urheber	Abadie, Diamond & Hainmueller (2010); extended to multi-period settings by Abadie (2021) and Ben-Michael et al. (2021)	Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
Typ	Quasi-experimental causal inference	Causal inference / panel regression
Wegweisende Quelle	Abadie, A. (2021). Using synthetic controls: Feasibility, data requirements, and methodological aspects. Journal of Economic Literature, 59(2), 391-425.	Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Aliasnamen	multi-period SCM, extended synthetic control, synthetic control with multiple treatment periods, staggered synthetic control	diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Verwandt	5	5
Zusammenfassung	The multi-period synthetic control method extends the classic synthetic control framework to settings where treatment occurs across several distinct periods or where the researcher needs to track causal effects over a prolonged post-treatment window. It constructs a weighted combination of untreated units that reproduces the treated unit's pre-treatment trajectory, then uses that synthetic counterfactual across all post-treatment periods to estimate time-varying treatment effects.	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.