The classical statistical model relates to n independent random variables having a common distribution. In this paper we consider the situation where the common distribution involves an unknown parameter, and where at time 0<t<1 only the first [nt] random variables are observed.

Diffuse priors lead to pathological posterior behaviour when used in Bayesian analyses of Simultaneous Equation Models (SEMs). This results from the local nonidentification of certain parameters in SEMs. When this, a priori known, feature is not captured appropriately, and a posteriori favour...