Regression model
Two-Stage Least Squares (2SLS / IV) Regression
Two-Stage Least Squares is a two-step instrumental-variables estimator that addresses endogeneity, the situation where a regressor is correlated with the error term. In the first stage the endogenous regressor is predicted from instrumental variables, and in the second stage the structural equation is estimated using those predictions. It is a central tool in applied econometrics, developed in textbook treatments such as Angrist and Pischke (2009).
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Sources
- Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Related methods
Referenced by
Bayesian Instrumental VariablesDynamic Instrumental VariablesFourier Hausman testFuzzy Regression DiscontinuityGeneralized Least SquaresGMM EstimationHeterogeneous treatment effect Instrumental variablesInstrumental Variables in Education ResearchMachine learning-augmented instrumental variablesMendelian RandomizationNonlinear difference GMMNonlinear Hausman testNonlinear System GMMPanel Data Instrumental VariablesPolicy Evaluation Instrumental VariablesRobust Instrumental VariablesRobust System GMMSeemingly Unrelated RegressionThree-Stage Least Squares