Document Type
Discussion Paper
Publication Date
2-1-2015
CFDP Number
1984R
CFDP Pages
34
Abstract
We derive mean-unbiased estimators for the structural parameter in instrumental variables models with a single endogenous regressor where the sign of one or more first stage coefficients is known. In the case with a single instrument, the unbiased estimator is unique. For cases with multiple instruments we propose a class of unbiased estimators and show that an estimator within this class is efficient when the instruments are strong. We show numerically that unbiasedness does not come at a cost of increased dispersion in models with a single instrument: in this case the unbiased estimator is less dispersed than the 2SLS estimator. Our finite-sample results apply to normal models with known variance for the reduced-form errors, and imply analogous results under weak instrument asymptotics with an unknown error distribution.
Recommended Citation
Andrews, Isaiah and Armstrong, Timothy B., "Unbiased Instrumental Variables Estimation under Known First-Stage Sign" (2015). Cowles Foundation Discussion Papers. 2407.
https://elischolar.library.yale.edu/cowles-discussion-paper-series/2407
Comments
Supplement Materials, 28 pp