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

C-Tier
Journal: Economics Letters
Year: 2018
Volume: 165
Issue: C
Pages: 10-12

Score contribution per author:

1.005 = (α=2.01 / 1 authors) × 0.5x C-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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.

Technical Details

RePEc Handle
repec:eee:ecolet:v:165:y:2018:i:c:p:10-12
Journal Field
General
Author Count
1
Added to Database
2026-01-25