Maximum-likelihood based inference in the two-way random effects model with serially correlated time effects
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
Volume (Year): 29 (2004)
Issue (Month): 1 (January)
|Contact details of provider:|| Web page: http://www.springer.com|
|Order Information:||Web: http://www.springer.com/economics/econometrics/journal/181/PS2|
When requesting a correction, please mention this item's handle: RePEc:spr:empeco:v:29:y:2004:i:1:p:79-88. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla)or (Rebekah McClure)
If references are entirely missing, you can add them using this form.