State Space Modelling of Cointegrated Systems using Subspace Algorithms
AbstractThe use of subspace algorithms for the identification of non-stationary cointegrated stochastic systems is a promising technique that is currently under discussion. A revision of the literature provides two distinct algorithms: State Space Aoki Time Series (SSATS) identification algorithm (Aoki and Havenner 1991) and the Adapted Canonical Correlations Analysis (ACCA) of Bauer and Wagner (2002). Aoki's method is intuitively appealing, but lacks statistical foundation. In contrast, ACCA has a sound statistical basis, though intuition is somewhat lost. Both algorithms are revisited and commented. The study of the underlying ideas and properties of both previous algorithms leads us to propose a new method for subspace identification of non-stationary cointegrated stochastic systems, trying to combine the best features of each one. This new method provides a state space trend-cycle representation of a cointegrated system. Some preliminary simulation results are summarised, comparing these subspace methods with Johansen's maximum likelihood approach.
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Bibliographic InfoPaper provided by EconWPA in its series Econometrics with number 0509010.
Length: 11 pages
Date of creation: 06 Sep 2005
Date of revision: 07 Feb 2006
Note: Type of Document - pdf; pages: 11
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system identification; state space; subspace; cointegration; CCA;
Find related papers by JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-11-09 (All new papers)
- NEP-ECM-2005-11-09 (Econometrics)
- NEP-ETS-2005-11-09 (Econometric Time Series)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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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- José Mondéjar Jiménez & Manuel Vargas Vargas, 2006. "Análisis de tendencias comunes y cointegración en espacio de estados," Contribuciones a la Economía, Grupo Eumed.net (Universidad de Málaga), issue 2006-09, September.
- Gonzalo, Jesus, 1994. "Five alternative methods of estimating long-run equilibrium relationships," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 203-233.
- Dietmar Bauer & Martin Wagner, 2003. "The Performance of Subspace Algorithm Cointegration Analysis: A Simulation Study," Diskussionsschriften dp0308, Universitaet Bern, Departement Volkswirtschaft.
- Wagner, Martin, 1999. "VAR Cointegration in VARMA Models," Economics Series 65, Institute for Advanced Studies.
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