Estimating Bayesian Decision Problems with Heterogeneous Priors∗

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 un-derlying theoretical voting model, we suggest estimates of the structural parame-ters based on their methodology should generally benefit from including interaction terms between individual and time covariates in the first stage whenever there is individual heterogeneity in expertise. We show numerically, via simulation and re-estimation of the US Supreme Court data, that the first order interaction effects that appear in the theoretical model can have an important empirical implication