Maximun entropy Leuven estimators and multicollinearity

Abstract

A novel class of estimators, called maximum entropy Leuven (MEL) estimators, is presented and its performance is illustrated by Monte Carlo experiments. These estimators are inspired by the theory of light. The MEL estimators are consistent and asymptotically normal. They rival the generalized maximum entropy estimator (GME). Based on the mean squared error criterion, the MEL estimators outperform the ordinary least-squares estimator in the presence of multicollinerity.