Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10327824 | Computational Statistics & Data Analysis | 2005 | 16 Pages |
Abstract
New iterative reduced-rank regression procedures for seasonal cointegration analysis were proposed. The suggested methods are motivated by the idea that modelling the cointegration restrictions jointly at different frequencies may increase efficiency in finite samples. Monte Carlo simulations indicate that the new tests and estimators perform well with respect to already existing statistical procedures.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Gianluca Cubadda, Pieter Omtzigt,