A Simple Improvement of the IV‐estimator for the Classical Errors‐in‐Variables Problem

Two measures of an error‐ridden variable make it possible to solve the classical errors‐in‐Variable problem by using one measure as an instrument for the other. It is well known that a second IV‐estimate can be obtained by reversing the roles of the two measures. We explore the optimal linear combination of these two estimates. In a Monte Carlo study, we show that the gain in precision is significant. The proposed estimator also compares well with full information maximum likelihood under normality. We illustrate the method by estimating the capital elasticity in the Norwegian ICT‐industry.