Maximum-likelihood based inference in the two-way random effects model with serially correlated time effects

Sune Karlsson () and Jimmy Skoglund ()

Empirical Economics, 2004, vol. 29, issue 1, pages 79-88

Abstract: The 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

Keywords: Panel data; autocorrelation; time specific effect; variance components; C12; C13; C23; C51 (search for similar items in EconPapers)
View citations in EconPapers

Downloads: (external link)
http://hdl.handle.net/10.1007/s00181-003-0190-4 (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Maximum-Likelihood Based Inference in the Two-Way Random Effects Model with Serially Correlated Time Effects (2000)
Working Paper: Maximum-likelihood based inference in the two-way random effects model with serially correlated time effects (2000)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Ordering information: This journal article can be ordered from
http://link.springer.de/orders.htm

Access Statistics for this article

Empirical Economics is edited by Badi H. Baltagi, Heather M. Anderson and Bernd Fitzenberger

More articles in Empirical Economics from Springer
Series data maintained by Christopher F Baum ().