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Cointegration in a periodic vector autoregression

Author

Listed:
  • Kleibergen, F.R.
  • Franses, Ph.H.B.F.

Abstract

We consider representation, estimation and inference on cointegration in a (PVAR). We show that cointegration amounts to a restriction on a product of parameter matrices. We therefore use GMM to construct estimators of the long-run (cointegration) parameters and to obtain test statistics for cointegration. We show that the limiting distributions of the GMM estimators and the corresponding test statistics in a PVAR are identical to those of the maximum likelihood cointegration estimators and test statistics in standard nonperiodic VAR models.

Suggested Citation

  • Kleibergen, F.R. & Franses, Ph.H.B.F., 1999. "Cointegration in a periodic vector autoregression," Econometric Institute Research Papers EI 9906-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:1561
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    Cited by:

    1. Lof, Marten & Hans Franses, Philip, 2001. "On forecasting cointegrated seasonal time series," International Journal of Forecasting, Elsevier, vol. 17(4), pages 607-621.
    2. del Barrio Castro, Tomás, 2021. "Testing for the cointegration rank between Periodically Integrated processes," MPRA Paper 106603, University Library of Munich, Germany, revised 2021.
    3. del Barrio Castro, Tomás, 2021. "Testing for the cointegration rank between Periodically Integrated processes," MPRA Paper 106603, University Library of Munich, Germany, revised 2021.

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