The error components model: Conditions for the existence of the maximum likelihood estimates

The paper provides a stochastic specification of the error components model that ensures a positive maximum likelihood estimate of the error component variance. Also, it is shown that all of the stochastic parameters of the error components are identifiable albeit with certain qualifications. The model analyzed is the simple, two-component model, in which the stochastic variable is decomposed into a random individual effect and an overall error term. However, the results can be easily generalized to include an additional random time-effect variable.