7.5 Summary

In this chapter, we present the setting and posterior distributions of the most common multivariate models. The multivariate framework allows us to address endogeneity issues by using the conditional distribution of a multivariate normal vector. Moreover, we always obtain posterior conditional distributions that belong to standard families (multivariate normal, Wishart, and truncated normal) in these models. This property enables the implementation of the Gibbs sampling algorithm for all these models.