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 uninformative confidence intervals.

The authors of this paper propose two new estimation approaches that strengthen the instrument. They derive their theoretical properties and show in Monte Carlo simulations that they outperform standard IV-estimators. The authors use these procedures to estimate the effect of public utility divestiture in the US nuclear energy sector. Their results show that divestiture significantly increases production efficiency.

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