Comparer des méthodes

	Tests placebo pour l'inférence causale	Design par Différence de Discontinuités
Domaine	Inférence causale	Inférence causale
Famille	Regression model	Regression model
Année d'origine	2010	2016
Auteur d'origine	Abadie, Diamond & Hainmueller (synthetic control placebos); Imbens & Lemieux (RDD validity)	Grembi, Nannicini & Troiano
Type	Falsification / robustness test family for causal inference	Hybrid quasi-experimental causal design (RDD + DID)
Source fondatrice	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.	Grembi, V., Nannicini, T. & Troiano, U. (2016). Do Fiscal Rules Matter? A Difference-in-Discontinuities Design. American Economic Journal: Applied Economics, 8(3), 1-30.
Alias	falsification tests, placebo checks, refutation tests, Plasebo Testleri — Nedensel Çıkarım Doğrulama	diff-in-disc, DiD-RDD, Süreksizliklerde Fark (Difference-in-Discontinuities)
Apparentées	5	5
Résumé	Placebo tests are a family of falsification checks that probe the credibility of a causal claim by re-running the analysis on a fake treatment, a false intervention date, or an outcome that should not have been affected. The approach was popularised through the synthetic control work of Abadie, Diamond and Hainmueller (2010) and the regression-discontinuity validity checks of Imbens and Lemieux (2008).	Difference-in-Discontinuities is a hybrid quasi-experimental design that fuses regression discontinuity (RDD) with difference-in-differences (DID), introduced by Grembi, Nannicini and Troiano (2016). It compares the discontinuity at the same cutoff value across two periods to isolate a causal effect.