Abstract
This paper considers a feasible two-step estimator for seasonal cointegration as the extension of <TEX>$Br{\ddot{u}}ggeman$</TEX> and <TEX>$L{\ddot{u}}tkepohl$</TEX> (2005). It is shown that the reducedrank maximum likelihood(ML) estimator for seasonal cointegration can still produce occasional outliers as that for non-seasonal cointegration even though the sizes of them are not extreme as those in non-seasonal cointegration. The ML estimator(MLE) is compared with the two-step estimator in a small Monte Carlo simulation study and we find that the two-step estimator can be an attractive alternative to the MLE, especially, in a small sample.
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