On the efficient use of the informational content of estimating equations: Implied probabilities and Euclidean empirical likelihood
A number of information-theoretic alternatives to GMM have recently been proposed in the literature. For practical use and general interpretation, the main drawback of these alternatives, particularly in the case of conditional moment restrictions, is that they rely on high dimensional convex optimization programs. The main contribution of this paper is to analyze the informational content of estimating equations within the unified framework of least squares projections. Improved inference by control variables, shrinkage of implied probabilities and information-theoretic interpretations of continuously updated GMM are discussed in the two cases of unconditional and conditional moment restrictions. Plusieurs méthodes alternatives à GMM basées sur un critère d'information ont récemment été proposées. Pour leur utilisation pratique et leur interprétation, le principal défaut de ces alternatives, particulièrement dans le cas de restrictions de moments conditionnels, est de faire appel à des programmes d'optimisation convexe de très grande dimension. La contribution principale de cet article est d'analyser le contenu informatif d'équations estimantes dans le cadre unifié de projections de moindres carrés. L'amélioration de l'inférence par variables de contrôle, le calcul des probabilités impliquées et les interprétations informationnelles des différentes versions de GMM sont discutés dans les deux cadres de moments conditionnels et inconditionnels.
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