Likelihood Estimation for Censored Random Vectors

Abstract

This article shows how to construct a likelihood for a general class of censoring problems. This likelihood is proven to be valid, i.e. its maximiser is consistent and the respective root-n estimator is asymptotically efficient and normally distributed under regularity conditions. The method generalises ordinary maximum likelihood estimation as well as several standard estimators for censoring problems (e.g. tobit type I - tobit type V).Censored variables; Limited dependent variables; Multivariate methods; Random censoring; Likelihood