© 1984

Bayesian Full Information Analysis of Simultaneous Equation Models Using Integration by Monte Carlo


Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 232)

Table of contents

  1. Front Matter
    Pages N2-VI
  2. Luc Bauwens
    Pages 1-3
  3. Luc Bauwens
    Pages 4-7
  4. Luc Bauwens
    Pages 21-34
  5. Luc Bauwens
    Pages 35-66
  6. Luc Bauwens
    Pages 67-69
  7. Luc Bauwens
    Pages 70-70
  8. Back Matter
    Pages 71-117

About this book


In their review of the "Bayesian analysis of simultaneous equation systems", Dr~ze and Richard (1983) - hereafter DR - express the following viewpoint about the present state of development of the Bayesian full information analysis of such sys­ tems i) the method allows "a flexible specification of the prior density, including well defined noninformative prior measures"; ii) it yields "exact finite sample posterior and predictive densities". However, they call for further developments so that these densities can be eval­ uated through 'numerical methods, using an integrated software packa~e. To that end, they recommend the use of a Monte Carlo technique, since van Dijk and Kloek (1980) have demonstrated that "the integrations can be done and how they are done". In this monograph, we explain how we contribute to achieve the developments suggested by Dr~ze and Richard. A basic idea is to use known properties of the porterior density of the param­ eters of the structural form to design the importance functions, i. e. approximations of the posterior density, that are needed for organizing the integrations.


Analysis Information Integration Likelihood calculus statistical model

Authors and affiliations

  1. 1.C.O.R.E.Louvain-La-NeuveBelgium

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