Bayesian Full Information Analysis of the Simultaneous Equations Model

  • J.-A. Morales
Part of the Lecture Notes in Operations Research and Mathematical Systems book series (LNE, volume 43)


Let observations be generated by the following system of structural equations:
$$ By\left( t \right)\; + \;\Gamma z\left( t \right) = u\left( t \right) $$
where y(t) is an m dimensional vector of endogenous variables, z(t) is an n-dimensional vector of truly exogenous variables, B is an m × m non-singular matrix of coefficients with diagonal elements Bii = 1, i = 1,2,…,m, г is an m × n matrix of coefficients and u(t) is an m-dimensional vector of unobservable random disturbances with a non-degenerate joint distribution.1


Posterior Density Marginal Density Prior Density Positive Definite Symmetric Matrix Simultaneous Equation Model 
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  1. 1.
    Drèze (10),(11).Google Scholar
  2. 1.
    Rothenberg (24)Google Scholar

Copyright information

© Springer-Verlag Berlin · Heidelberg 1971

Authors and Affiliations

  • J.-A. Morales
    • 1
  1. 1.Center for Operations Research and EconometricsUniversité Catholique de LouvainBelgique

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