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Identification and estimation using heteroscedasticity without instruments: The binary endogenous regressor case

Arthur Lewbel ()

Economics Letters, 2018, vol. 165, issue C, 10-12

Abstract: Lewbel (2012) provides an estimator for linear regression models containing an endogenous regressor, when no outside instruments or other such information is available. The method works by exploiting model heteroscedasticity to construct instruments using the available regressors. Some authors have considered the method in empirical applications where an endogenous regressor is binary (e.g., endogenous Diff-in-Diff or endogenous binary treatment models). The present paper shows that the assumptions required for Lewbel’s estimator can indeed be satisfied when an endogenous regressor is binary. Caveats regarding application of the estimator are discussed.

Keywords: Simultaneous systems; Linear regressions; Endogeneity; Identification; Heteroscedasticity; Binary regressors (search for similar items in EconPapers)
JEL-codes: C35 C36 C30 C13 (search for similar items in EconPapers)
Date: 2018
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Working Paper: Identification and Estimation Using Heteroscedasticity Without Instruments: The Binary Endogenous Regressor Case (2016) Downloads
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