Bayesian analysis of the SUR Tobit model

This paper develops a practical sampling scheme for Bayesian analysis of co rrelated censored data using the seemingly unrelated Tobit regressions mode l. Posterior inference is performed via the Gibbs sampler with data augment ation algorithm. In particular, the relevant full conditional distributions needed in the use of Gibbs sampler are derived. The method is then applied to a real data set on the determination of the payments of cash and stock dividends.