Before revision:  In a two-stage linear regression model with Normal noise, I consider James-Stein type shrinkage in the estimation of the first-stage instrumental variable coefficients.
After revision: The two-stage least-squares (2SLS) estimator is known to be biased when its first-stage fit is poor. I show that better first-stage prediction can alleviate this bias. In a two-stage linear regression model with Normal noise, I consider James-Stein type shrinkage in the estimation of the first-stage instrumental variable coefficients.