Lecture Notes in Economic and Mathematical Systems

I. Bayesian Full Information Analysis of the Simultaneous Equations Model.- 1. A review of the problem of identification in a Bayesian approach and the specifications of the prior density functions.- 1.1. The statistical model and notation.- 1.2. The problem of identification in a Bayesian context and the choice of prior distributions.- 2. The extended natural conjugate density and its properties.- 2.1. The extended natural conjugate density of all the parameters of the model.- 2.2. The extended natural conjugate density bearing on the parameters of a model with prior exclusion restrictions.- 2.3. Interpretation of the extended natural conjugate density.- 3. Posterior distributions of the structural parameters (?, ?-1).- 3.1. The joint a posteriori density of (?, ?-1).- 3.2. The marginal density function of ?.- Appendix to Part I. Some properties of the Wishart density function and the matric variate-t-density function.- II. Empirical illustration of a Bayesian Full Information Analysis. The analysis of the Belgian beef market.- 1. The model and the a priori information.- 1.1. The model of Calicis.- 1.2. Two equations models for the Belgian beef market.- 1.3. The likelihood function and the a priori density function.- 1.4. A description of the sources of prior-information.- 1.5. The complete specification of the prior density function.- 2. The Posterior Analysis.- 2.1. The posterior distributions.- 2.2. Comments on the results of the posterior analysis.- Conclusions.- References.