Bayesian interpretation of Generalized empirical likelihood by maximum entropy
Statistics Theory
2012-03-02 v1 Statistics Theory
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.
Cite
@article{arxiv.1202.6469,
title = {Bayesian interpretation of Generalized empirical likelihood by maximum entropy},
author = {Paul Rochet},
journal= {arXiv preprint arXiv:1202.6469},
year = {2012}
}