Compara mètodes

	Disseny de Regressió amb Punt d'Inflexió (RKD)	Regressió per Mínims Quadrats Ordinàris (MQO)
Camp	Inferència causal	Econometria
Família	Regression model	Regression model
Any d'origen	2015	2019
Autor original	Card, Lee, Pei & Weber	Wooldridge (textbook treatment); classical least squares
Tipus	Quasi-experimental design (slope-based RDD)	Linear regression
Font seminal	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
Àlies	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
Relacionats	4	5
Resum	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).