Bayesian method of moments (BMOM) analysis of parametric and semi-parametric regression models

Abstract

The Bayesian Method of Moments is applied to standard regression models using alternative series expansions of an unknown regression function. We descriptionbe estimation loss functions, predictive loss functions and posterior odds as techniques to determine how many terms in a particular expansion to keep and how to choose among different types of expansions. the developed theory is then applied in a Monte-Carlo experiment to data generated from a CES production function.