Comparer des méthodes

	Variables instrumentales par moindres carrés en deux étapes (VI/2SLS)	Régression par Moindres Carrés Ordinaires (MCO)
Domaine	Inférence causale	Économétrie
Famille	Regression model	Regression model
Année d'origine	2009	2019
Auteur d'origine	Angrist & Pischke (textbook treatment); Stock & Yogo (weak-instrument theory)	Wooldridge (textbook treatment); classical least squares
Type	Instrumental-variables regression	Linear regression
Source fondatrice	Angrist, J. D. & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Alias	instrumental variables, IV estimation, 2SLS, instrumental variable regression	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Apparentées	5	5
Résumé	IV/2SLS is a two-stage estimation method that recovers the causal effect of an endogenous regressor by isolating the part of its variation driven by an external instrument. It is the workhorse identification strategy in modern applied econometrics, developed at length in Angrist and Pischke's Mostly Harmless Econometrics (2009).	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).