This paper derives conditions under which the generalized method of moments (GMM) estimator is as efficient as the maximum likelihood estimator (MLE). The data are supposed to be drawn from a parametric family and to be stationary Markov. We study the efficiency of GMM in a general framework...

In many circumstances, the likelihood function does not have a simple tractable expression. The main examples discussed in the paper are the convolution and the mixture of distributions. Finite mixture models are commonly used to model data from a population composed of a finite number of...