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Posterior moments of elasticities between real wages and unemployment in Belgium : an application of Bayesian inference by Monte Carlo integration*
Published online by Cambridge University Press: 17 August 2016
Extract
Some 20 years ago, J. Drèze (1962) opened a new prospect for the statistical treatment of the « simultaneous equation model » in econometrics (SEM). Indeed, he advocated the use of Bayesian methods for the analysis of such models. In particular, he pointed out the flexibility of this approach as it allows to take account not only of the a priori information provided by economic theory or observation, but more fundamentally, of the imprecise nature of this kind of information.
Ever since, it has been clear that the Bayesian approach of the SEM would be rather difficult to implement. The main problems one can identify are
1. the representation of a priori information by a prior density function which should be easily interpretable and at the same time flexible enough;
2. the numerical treatment (i.e. integration) of the posterior density so as to obtain moments and marginal densities of parameters, whether they be parameters of the structural form, of the reduced form, or functions thereof.
- Type
- Research Article
- Information
- Recherches Économiques de Louvain/ Louvain Economic Review , Volume 49 , Issue 1 , March 1983 , pp. 47 - 59
- Copyright
- Copyright © Université catholique de Louvain, Institut de recherches économiques et sociales 1983
Footnotes
This text is the written version of my public lecture for obtaining a Ph. D. degree in economics at the Catholic University of Louvain. I wish to thank Professor J.-F. Richard for his encouragements and fruitful advises during the course of this research. Financial support of the « Projet d’Action Concertée » of the government of Belgium under contract 80/85-12 is gratefully acknowledged.
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