Asymptotics for Random Effects Models with Serial Correlation
Posted: 30 Mar 2013
Date Written: March 28, 2001
This paper considers the large sample behavior of the maximum likelihood estimator of random effects models. Consistent estimation and asymptotic normality as N and/or T grows large is established for a comprehensive specification which allows for serial correlation in the form of AR(1) for the idiosyncratic or time-specific error component. The consistency and asymptotic normality properties of all commonly used random effects models are obtained as special cases of the comprehensive model. When N or T >infty only a subset of the parameters are consistent and asymptotic normality is established for the consistent subsets.
Keywords: error component, maximum likelihood, asymptotic behavior
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