Methods for strengthening a weak instrument in the case of a persistent treatment

Abstract

Abstract When evaluating policy treatments that are persistent and endogenous, available instrumental variables often exhibit more variation over time than the treatment variable. This leads to a weak instrumental variable problem, resulting in high bias or uninformative confidence intervals. We evaluate two new estimation approaches that strengthen the instrument. We derive their theoretical properties and show in Monte Carlo simulations that they outperform standard IV-estimators. We use our procedures to estimate the effect of public utility divestiture in the US nuclear energy sector. Our results show that divestiture significantly increases production efficiency.