Likelihood Analysis of Seasonal Cointegration
The vector autoregressive model for seasonal cointegration is analysed. The general error correction model is discussed and conditions are found under which the process is integrated of order 1 at seasonal frequency and exhibits cointegration. Under these conditions a representation theorem for the solution is given expressed in terms of seasonal random walks. Finally the asymptotic properties of the likelihood ratio test for cointegrating rank is given, and it is shown that the estimated cointegrating vectors are asymptotically mixed Gaussian. The results resemble the result for cointegration at zero frequency but expressed in terms of a complex Brownian motion. Tables are provided for asymptotic inference under various assumptions on the deterministic terms.
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- Franses, Ph.H.B.F. & Kunst, R.M., 1998.
"On the role of seasonal intercepts in seasonal cointegration,"
Econometric Institute Research Papers
EI 9820, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Franses, Philip Hans & Kunst, Robert M, 1999. " On the Role of Seasonal Intercepts in Seasonal Cointegration," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(3), pages 409-433, August.
- Franses, Philip Hans & Kunst, Robert M., 1995. "On the role of seasonal intercepts in seasonal cointegration," Economics Series 15, Institute for Advanced Studies.
- Lee, Hahn Shik, 1992. "Maximum likelihood inference on cointegration and seasonal cointegration," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 1-47.
- Hylleberg, S. & Engle, R.F. & Granger, C.W.J. & Yoo, B.S., 1988.
"Seasonal, Integration And Cointegration,"
6-88-2, Pennsylvania State - Department of Economics.
- Osborn, Denise R., 1993. "Seasonal cointegration," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 299-303.
- Harbo, Ingrid, et al, 1998. "Asymptotic Inference on Cointegrating Rank in Partial Systems," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(4), pages 388-399, October.
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