Likelihood Analysis of Seasonal Cointegration

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The error correction model for seasonal cointegration is analyzed. Conditions are found under which the process is integrated of order 1 and cointegrated at seasonal frequency, and a representation theorem is given. The likelihood function is analyzed and the numerical calculation of the maximum likelihood estimators is discussed. The asymptotic distribution of the likelihood ratio test for cointegrating rank is given. It is shown that the estimated cointegrating vectors are asymptotically mixed Gaussian. The results resemble the results for cointegration at zero frequency when expressed in terms of a complex Brownian motion. Tables are provided for asymptotic inference.
Original languageEnglish
JournalJournal of Econometrics
Volume88
Issue number2
Pages (from-to)301-339
Number of pages39
ISSN0304-4076
DOIs
Publication statusPublished - 1999

    Research areas

  • Faculty of Social Sciences - autoregressive process, Granger’s theorem, error correction model, complex Brownian motion

ID: 9969138