Morales | Bayesian Full Information Structrual Analysis | Buch | 978-3-540-05417-7 | sack.de

Buch, Englisch, Band 43, 160 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 329 g

Reihe: Lecture Notes in Economics and Mathematical Systems

Morales

Bayesian Full Information Structrual Analysis

with an Application to the Study of the Belgian Beef Market
Softcover Nachdruck of the original 1. Auflage 1971
ISBN: 978-3-540-05417-7
Verlag: Springer Berlin Heidelberg

with an Application to the Study of the Belgian Beef Market

Buch, Englisch, Band 43, 160 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 329 g

Reihe: Lecture Notes in Economics and Mathematical Systems

ISBN: 978-3-540-05417-7
Verlag: Springer Berlin Heidelberg


1 1. Statement of the problem. Bayes' theorem provides a very powerful tool for statistical inference, especially when pooling information from different sources is appropriate. Thus, prior information resulting from economic theory and/or from previous (real or hypothetical) samples can be combined with the information embodied in new observations; and this operation can be performed formally, within a rigorous mathematical framework. To introduce the Bayesian analysis of the simultaneous equations model, we shall base our presentation in the very convenient exposition given by Dreze in his presidential adress to the. S' 2 C f Second World ongress 0 the Econometr1c oC1ety. The Bayesian method in statistics is usually presented as follows Consider the joint probability density function f(x.e) defined on the product space X x9, where X = {x} denotes the sample space, and e = {e} denotes the parameter space, If we decompose the joint density f(x,e) in a conditional density f(x/e) and a marginal lThe beginning of this section reviews some very well known proposi­ tions of Bayesian analysis. Those who are familiar with the subject can skip this part, and start with p.5. 2J.H.Dreze. "Econometrics and Decision Theory". Presidential adress delivered at the Second World Congress of the Econometric Society.

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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.- 2. The extended natural conjugate density and its properties.- 3. Posterior distributions of the structural parameters (?, ?-1).- 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.- 2. The Posterior Analysis.- Conclusions.- References.



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