Maximum-likelihood based inference in the two-way random effects model with serially correlated time effects
AbstractThe general case where the time specific effect in a two way model follows an arbitrary ARMA process has not been considered previously. We offer a straightforward maximum likelihood estimator for this case. Allowing for general ARMA processes raises the issue of model specification and we propose tests of the null hypothesis of no serial correlation as well as tests for discriminating between different specifications. A Monte-Carlo experiment evaluates the finite-sample properties of the estimators and test-statistics. Copyright Springer-Verlag 2004
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Bibliographic InfoArticle provided by Springer in its journal Empirical Economics.
Volume (Year): 29 (2004)
Issue (Month): 1 (January)
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Other versions of this item:
- Sune Karlsson & Jimmy Skoglund, 2000. "Maximum-Likelihood Based Inference in the Two-Way Random Effects Model with Serially Correlated Time Effects," Econometric Society World Congress 2000 Contributed Papers 1178, Econometric Society.
- Karlsson, Sune & Skoglund, Jimmy, 2000. "Maximum-likelihood based inference in the two-way random effects model with serially correlated time effects," Working Paper Series in Economics and Finance 383, Stockholm School of Economics.
- 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
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
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