Estimating cointegrated systems using subspace algorithms
In this paper the properties of so called subspace methods in the context of cointegrated processes of order one are investigated. It is shown that the algorithms deliver consistent estimates of the transfer function in the case of general VARMA models and under mild conditions on the underlying noise process. A procedure for the estimation of the dimension of the cointegrating space is presented and consistency for this procedure is proven. Also the estimation of the order of the system is discussed. Simulation examples demon- strate the usefulness of the subspace algorithms for the estimation of cointegrated systems.
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- Bauer, Dietmar & Wagner, Martin, 2002.
"Estimating cointegrated systems using subspace algorithms,"
Journal of Econometrics,
Elsevier, vol. 111(1), pages 47-84, November.
- Dietmar Bauer & Martin Wagner, 2000. "Estimating Cointegrated Systems Using Subspace Algorithms," Econometric Society World Congress 2000 Contributed Papers 0293, Econometric Society.
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- H. Lütkepohl & P. Saikkonen, 1995. "Impulse Response Analysis in Infinite Order Cointegrated Vector Autoregressive Processes," SFB 373 Discussion Papers 1995,11, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
- Bierens, Herman J., 1997. "Nonparametric cointegration analysis," Journal of Econometrics, Elsevier, vol. 77(2), pages 379-404, April.
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- Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254. Full references (including those not matched with items on IDEAS)
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