Work

Bayesian interpretation of Generalized empirical likelihood by maximum entropy

Year: 2012

Type: preprint

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.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.1202.6469

Author: Rochet, Paul

Institutions: Université Toulouse III - Paul Sabatier, Institut National des Sciences Appliquées de Toulouse, Institut de Mathématiques de Toulouse

Language: English

Topic: Statistical Methods and Bayesian Inference

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W1619465883

Cites: 14

Cited by:

Related to: 10