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On the Asymptotic Properties of Estimators of Models Containing Limited Dependent Variables

Peter M. Robinson

Abstract

For the Tobit model with independent observations, Amemiya [1] has established the strong consistency and asymptotic normality of a stationary point, @Q, of the log-likelihood. The likelihood for dependent observations may be computationally intractable, so the behavior of @Q in the presence of serially correlated observations is of interest. Under a relaxation of Amemiya's assumption of independence, we prove that @Q is strongly consistent and asymptotically normal, and give an expression for the limiting covariance matrix.