Comparer des méthodes

	La conception à point d'inflexion de régression (Regression Kink Design - RKD)	Régression par Moindres Carrés Ordinaires (MCO)
Domaine	Inférence causale	Économétrie
Famille	Regression model	Regression model
Année d'origine	2015	2019
Auteur d'origine	Card, Lee, Pei & Weber	Wooldridge (textbook treatment); classical least squares
Type	Quasi-experimental design (slope-based RDD)	Linear regression
Source fondatrice	Card, D., Lee, D. S., Pei, Z. & Weber, A. (2015). Inference on Causal Effects in a Generalized Regression Kink Design. Econometrica, 83(6), 2453-2483.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Alias	RKD, regression kink design, kink regression discontinuity, Regresyon Kırılma Tasarımı (RKD — Regression Kink Design)	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Apparentées	4	5
Résumé	The Regression Kink Design is a quasi-experimental method that estimates a causal effect when a policy rule creates a change in slope (a kink) — rather than a jump — at a known threshold of a running variable. It was formalised as a generalized design by Card, Lee, Pei and Weber (2015) and is the slope-based counterpart of the regression discontinuity design.	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).