Priors and posterior computation in linear endogenous variable models with imperfect instruments
In this paper we, like several studies in the recent literature, employ a Bayesian approach to estimation and inference in models with endogeneity concerns by imposing weaker prior assumptions than complete excludability. When allowing for instrument imperfection of this type, the model is only partially identified, and as a consequence standard estimates obtained from the Gibbs simulations can be unacceptably imprecise. We thus describe a substantially improved 'semi-analytic' method for...[Show more]
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|Source:||Journal of Applied Econometrics|
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