Bayesian interpretation of Generalized empirical likelihood by maximum entropy

Abstract : We study a parametric estimation problem related to moment condition models. As an alternative to the generalized empirical likelihood (GEL) and the generalized method of moments (GMM), a Bayesian approach to the problem can be adopted, extending the MEM procedure to parametric moment conditions. We show in particular that a large number of GEL estimators can be interpreted as a maximum entropy solution. Moreover, we provide a more general field of applications by proving the method to be robust to approximate moment conditions.
Type de document :
Pré-publication, Document de travail
2011


https://hal.archives-ouvertes.fr/hal-00675044
Contributeur : Paul Rochet <>
Soumis le : mardi 28 février 2012 - 19:05:20
Dernière modification le : lundi 7 décembre 2015 - 14:17:57
Document(s) archivé(s) le : mardi 29 mai 2012 - 02:41:15

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  • HAL Id : hal-00675044, version 1
  • ARXIV : 1202.6469

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Paul Rochet. Bayesian interpretation of Generalized empirical likelihood by maximum entropy. 2011. <hal-00675044>

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