IDEAS home Printed from https://ideas.repec.org/p/wpa/wuwpem/0509010.html
   My bibliography  Save this paper

State Space Modelling of Cointegrated Systems using Subspace Algorithms

Author

Listed:
  • Segismundo Izquierdo

    (University of Valladolid)

  • Ces�reo Hern�ndez

    (University of Valladolid)

  • Javier Pajares

    (University of Valladolid)

Abstract

The 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.

Suggested Citation

  • Segismundo Izquierdo & Ces�reo Hern�ndez & Javier Pajares, 2005. "State Space Modelling of Cointegrated Systems using Subspace Algorithms," Econometrics 0509010, University Library of Munich, Germany, revised 07 Feb 2006.
    • Handle: RePEc:wpa:wuwpem:0509010
    Note: Type of Document - pdf; pages: 11
    as

    Download full text from publisher

    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/em/papers/0509/0509010.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wagner, Martin, 1999. "VAR Cointegration in VARMA Models," Economics Series 65, Institute for Advanced Studies.
    2. Bauer, Dietmar & Wagner, Martin, 2002. "Estimating cointegrated systems using subspace algorithms," Journal of Econometrics, Elsevier, vol. 111(1), pages 47-84, November.
    3. José Mondéjar Jiménez & Manuel Vargas Vargas, 2006. "Análisis de tendencias comunes y cointegración en espacio de estados," Contribuciones a la Economía, Servicios Académicos Intercontinentales SL, issue 2006-09, September.
    4. Gonzalo, Jesus, 1994. "Five alternative methods of estimating long-run equilibrium relationships," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 203-233.
    5. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    6. Dietmar Bauer & Martin Wagner, 2003. "The Performance of Subspace Algorithm Cointegration Analysis: A Simulation Study," Diskussionsschriften dp0308, Universitaet Bern, Departement Volkswirtschaft.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Izquierdo, Segismundo S. & Hernández, Cesáreo & del Hoyo, Juan, 2006. "Forecasting VARMA processes using VAR models and subspace-based state space models," MPRA Paper 4235, University Library of Munich, Germany.
    2. Martin Wagner, 2004. "A Comparison of Johansen's, Bierens’ and the Subspace Algorithm Method for Cointegration Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(3), pages 399-424, July.
    3. Bauer, Dietmar & Wagner, Martin, 2002. "Estimating cointegrated systems using subspace algorithms," Journal of Econometrics, Elsevier, vol. 111(1), pages 47-84, November.
    4. Law, Siong Hook & Tan, Hui & baharumshah, ahmad, 1999. "Financial Liberalization in ASEAN and the Fisher Hypothesis," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 33, pages 65-86.
    5. Mauricio, Jose Alberto, 2006. "Exact maximum likelihood estimation of partially nonstationary vector ARMA models," Computational Statistics & Data Analysis, Elsevier, vol. 50(12), pages 3644-3662, August.
    6. Tang, Chor Foon & Tan, Eu Chye, 2015. "Does tourism effectively stimulate Malaysia's economic growth?," Tourism Management, Elsevier, vol. 46(C), pages 158-163.
    7. Michael S. Haigh & David A. Bessler, 2004. "Causality and Price Discovery: An Application of Directed Acyclic Graphs," The Journal of Business, University of Chicago Press, vol. 77(4), pages 1099-1121, October.
    8. Chow, Sheung Chi & Vieito, João Paulo & Wong, Wing Keung, 2019. "Do both demand-following and supply-leading theories hold true in developing countries?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 536-554.
    9. Levent KORAP, 2008. "Exchange Rate Determination Of Tl/Us$:A Co-Integration Approach," Istanbul University Econometrics and Statistics e-Journal, Department of Econometrics, Faculty of Economics, Istanbul University, vol. 7(1), pages 24-50, May.
    10. Onafowora, Olugbenga A. & Owoye, Oluwole, 1998. "Can Trade Liberalization Stimulate Economic Growth in Africa?," World Development, Elsevier, vol. 26(3), pages 497-506, March.
    11. Bernstein, Ronald & Madlener, Reinhard, 2015. "Short- and long-run electricity demand elasticities at the subsectoral level: A cointegration analysis for German manufacturing industries," Energy Economics, Elsevier, vol. 48(C), pages 178-187.
    12. Emmanouil Mavrakis & Christos Alexakis, 2018. "Statistical Arbitrage Strategies under Different Market Conditions: The Case of the Greek Banking Sector," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(2), pages 159-185, August.
    13. Irfan Civcir, 2003. "The Monetary Models of the Turkish Lira/U.S. Dollar Exchange Rate: Long-run Relationships, Short-run Dynamics, and Forecasting," Eastern European Economics, Taylor & Francis Journals, vol. 41(6), pages 43-63, January.
    14. Eleni Constantinou & Avo Kazandjian & Georgios P. Kouretas & Vera Tahmazian, 2008. "Common Stochastic Trends Among The Cyprus Stock Exchange And The Ase, Lse And Nyse," Bulletin of Economic Research, Wiley Blackwell, vol. 60(4), pages 327-349, October.
    15. Kausik Chaudhuri, 1997. "Stock returns in emerging markets: a common trend analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 4(2), pages 105-108.
    16. Urbain, Jean-Pierre, 1995. "Partial versus full system modelling of cointegrated systems an empirical illustration," Journal of Econometrics, Elsevier, vol. 69(1), pages 177-210, September.
    17. Haug, Alfred A., 1996. "Tests for cointegration a Monte Carlo comparison," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 89-115.
    18. Bremnes, Helge & Gjerde, Oystein & Saettem, Frode, 1997. "A multivariate cointegration analysis of interest rates in the Eurocurrency market," Journal of International Money and Finance, Elsevier, vol. 16(5), pages 767-778, September.
    19. Kühl, Michael, 2007. "Cointegration in the foreign exchange market and market efficiency since the introduction of the Euro: Evidence based on bivariate cointegration analyses," University of Göttingen Working Papers in Economics 68, University of Goettingen, Department of Economics.
    20. Mallory Mindy & Lence Sergio H., 2012. "Testing for Cointegration in the Presence of Moving Average Errors," Journal of Time Series Econometrics, De Gruyter, vol. 4(2), pages 1-68, November.

    More about this item

    Keywords

    system identification; state space; subspace; cointegration; CCA;
    All these keywords.

    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; State Space Models

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wpa:wuwpem:0509010. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: EconWPA (email available below). General contact details of provider: https://econwpa.ub.uni-muenchen.de .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.