Quasi-Maximum Likelihood Estimation

Abstract

The class of models discussed in Parts ONE and TWO of the book assume that the specification of the likelihood function, in terms of the joint probability distribution of the variables, is correct and that the regularity conditions set out in Chapter 2 are satisfied. Under these conditions, the maximum likelihood estimator has the desirable properties discussed in Chapter 2, namely that it is consistent, asymptotically normally distributed and asymptotically efficient because in the limit it achieves the Cramér-Rao lower bound given by the inverse of the information matrix.