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
