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Asymptotic properties of the maximum likelihood estimator of random effects models with serial correlation
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Abstract
This paper considers the large sample behavior of the maximum likelihood estimator of random effects models with serial correlation in the form of AR(1) for the idiosyncratic or time-specific error component. Consistent estimation and asymptotic normality as N and/or T grows large is established for a comprehensive specification which nests these models as well as all commonly used random effects models. When only N or T grows large only a subset of the parameters are consistent and asymptotic normality is established for the consistent subsets.Panel data; serial correlation; random effects