Seemingly Unrelated Time Series Equations and a Test for Homogeneity
Javier Fernandez-Macho and
Journal of Business & Economic Statistics, 1990, vol. 8, issue 1, 71-81
A multivariate structural time series model made up of unobserved components such as trends and seasonals is formulated. A homogeneous system, in which any linear combination of the observations follows the same time series process, is shown to correspond to a multivariate structural model in which the covariance matrices of the disturbances are proportional. A homogeneous model is considerably easier to estimate than the more general model and a score test of homogeneity can be constructed in the frequency domain. The finite-sample properties of this test are evaluated in a series of Monte Carlo experiments. Finally, a test of serial correlation for use in homogeneous systems is described.
References: Add references at CitEc
Citations: View citations in EconPapers (7) Track citations by RSS feed
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:bes:jnlbes:v:8:y:1990:i:1:p:71-81
Ordering information: This journal article can be ordered from
Access Statistics for this article
Journal of Business & Economic Statistics is currently edited by Jonathan H. Wright and Keisuke Hirano
More articles in Journal of Business & Economic Statistics from American Statistical Association
Bibliographic data for series maintained by Christopher F. Baum ().