Abstract
We consider the recent novel two-step estimator of Iaryczower and Shum (2012), who analyze voting decisions of US Supreme Court justices. Motivated by the underlying theoretical voting model, we suggest that where the data under consideration displays variation in the common prior, estimates of the structural parameters based on their methodology should generally benet from including interaction terms between individual and time covariates in the rst stage whenever there is individual heterogeneity in expertise. We show numerically, via simulation and re-estimation of the US Supreme Court data, that the rst order interaction eects that appear in the theoretical model can have an important empirical implication.
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