Asymptotic properties of the maximum likelihood estimator of random effects models with serial correlation
AbstractThis 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.
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Bibliographic InfoPaper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 0432.
Length: 47 pages
Date of creation: 13 Feb 2001
Date of revision:
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Panel data; serial correlation; random effects;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
This paper has been announced in the following NEP Reports:
- NEP-ECM-2001-03-16 (Econometrics)
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