Comparer des méthodes

	Design par Différence de Discontinuités	Régression par Moindres Carrés Ordinaires (MCO)
Domaine	Inférence causale	Économétrie
Famille	Regression model	Regression model
Année d'origine	2016	2019
Auteur d'origine	Grembi, Nannicini & Troiano	Wooldridge (textbook treatment); classical least squares
Type	Hybrid quasi-experimental causal design (RDD + DID)	Linear regression
Source fondatrice	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.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Alias	diff-in-disc, DiD-RDD, Süreksizliklerde Fark (Difference-in-Discontinuities)	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Apparentées	5	5
Résumé	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.	Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).