SSE/EFI Working Paper Series in Economics and Finance
No 383:
Maximum-likelihood based inference in the two-way random effects model with serially correlated time effects
Sune Karlsson ()
and Jimmy Skoglund ()
Abstract: This paper considers maximum likelihood estimation and
inference in the two-way random effects model with serial correlation. We
derive a straightforward maximum likelihood estimator when the
time-specific component follow an AR(1) or MA(1) process. The estimator is
easily generalized to arbitrary stationary and strictly invertible ARMA
processes. In addition we consider the model selection problem and derive
tests of the null hypothesis of no serial correlation as well as tests for
discriminating between the AR(1) and MA(1) specifications. A Monte-Carlo
experiment evaluates the finite-sample properties of the estimators,
test-statistics and model selection procedures.
Keywords: Panel data; autocorrelation; time specific effect; variance components; (follow links to similar papers)
JEL-Codes: C12; C13; C23; C51; (follow links to similar papers)
31 pages, May 15, 2000
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- This paper is published as:
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Karlsson, Sune and Jimmy Skoglund, (2004), 'Maximum-likelihood based inference in the two-way random effects model with serially correlated time effects', Empirical Economics, Vol. 29, pages 79-88
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