A Feasible Two-Step Estimator for Seasonal Cointegration

초록

This paper considers a feasible two-step estimator for seasonal cointegration asthe extension of Bruggemann and Lutkepohl (2005). It is shown that the reduced-rank maximum likelihood(ML) estimator for seasonal cointegration can still produceoccasional outliers as that for non-seasonal cointegration even though the sizes ofthem are not extreme as those in non-seasonal cointegration. The ML estima-tor(MLE) is compared with the two-step estimator in a small Monte Carlo simula-tion study and we nd that the two-step estimator can be an attractive alternativeto the MLE, especially, in a small sample.

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