Project the endogenous regressor
The first stage regresses the endogenous regressor on the instruments and exogenous controls. Its fitted values represent the component explained by those variables.
Ben Lambert · YouTube · 8:24
Introduce two-stage least squares for an endogenous regressor and explain why instrument quality matters.
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The first stage regresses the endogenous regressor on the instruments and exogenous controls. Its fitted values represent the component explained by those variables.
The second stage uses those fitted values in place of the endogenous regressor in the structural regression. Validity requires instrument exogeneity and sufficient relevance; ordinary second-stage standard errors alone are not generally the correct 2SLS uncertainty estimate.
The lesson warns that weak or redundant instruments can harm finite-sample behavior. Claims of improved efficiency need valid instruments and the corresponding model assumptions; first-stage strength should be assessed.
The first stage regresses the endogenous regressor on the instruments and exogenous controls. Its fitted values represent the component explained by those variables.
The second stage uses those fitted values in place of the endogenous regressor in the structural regression. Validity requires instrument exogeneity and sufficient relevance; ordinary second-stage standard errors alone are not generally the correct 2SLS uncertainty estimate.
The lesson warns that weak or redundant instruments can harm finite-sample behavior. Claims of improved efficiency need valid instruments and the corresponding model assumptions; first-stage strength should be assessed.
The first stage regresses the endogenous regressor on the instruments and exogenous controls. Its fitted values represent the component explained by those variables. The second stage uses those fitted values in place of the endogenous regressor in the structural regression. Validity requires instrument exogeneity and sufficient relevance; ordinary second-stage standard errors alone are not generally the correct 2SLS uncertainty estimate. The lesson warns that weak or redundant instruments can harm finite-sample behavior. Claims of improved efficiency need valid instruments and the corresponding model assumptions; first-stage strength should be assessed.