Extension to Markov processes of a result by A. Wald about the consistency of the maximum likelihood estimate

Summary In this note the proof of the consistency of a maximum likelihood estimate (MLE) obtained by Wald in [7] in the case of independent and identically distributed random variables is extended to the case of Markov processes.There is an extensive literature about the existence of a MLE and its consistency, most of which includes the assumption of the existence of derivatives of the densities with respect to the parameter involved. (See, for example, [2] and other references cited there.) Even under the rather strong assumption of pointwise differentiability of densities, and other additional regularity conditions, the problem of existence and consistency of a MLE has not been solved satisfactorily. (See, for example, [1], [2], [4], [6].) On the other hand, there have appeared papers like [3], where the consistency of a MLE is proved for processes with dependent random variables, and without the usual differentiability assumptions. The conditions used in the present paper are, however, of a different nature from those imposed in [3], and also are slightly different from Wald's assumptions in [7]. To our knowledge, a proof of consistency of a MLE under conditions similar to the ones used here has not appeared in the literature.I would like to take this opportunity to thank Professor L. LeCam for a number of remarks in connection with this paper.Prepared with the partial support of the National Science Foundation, Grant GP-10.