Asymptotics for random effects models with serial correlation
Jimmy Skoglund () and
Sune Karlsson ()
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Jimmy Skoglund: Department of Economic Statistics, Stockholm School of Economics
No A6-1, 10th International Conference on Panel Data, Berlin, July 5-6, 2002 from International Conferences on Panel Data
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 \rightarrow \infty only a subset of the parameters are consistent and asymptotic normality is established for the consistent subsets.
Keywords: Panel data; error components; consistency; asymptotic normality; maximum likelihood. (search for similar items in EconPapers)
JEL-codes: C12 C13 C23 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:cpd:pd2002:a6-1
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