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.
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Preprints, Working Papers, ...
2011


https://hal.archives-ouvertes.fr/hal-00675044
Contributor : Paul Rochet <>
Submitted on : Tuesday, February 28, 2012 - 7:05:20 PM
Last modification on : Wednesday, February 29, 2012 - 8:47:51 AM

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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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