Bayesian interpretation of Generalized empirical likelihood by maximum entropy

Paul Rochet

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arXiv · 1202.6469

Bayesian interpretation of Generalized empirical likelihood by maximum entropy

Paul Rochet

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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.

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Paul Rochet. 2012-02-29. Bayesian interpretation of Generalized empirical likelihood by maximum entropy. https://arxiv.org/abs/1202.6469

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