IDEAS home Printed from https://ideas.repec.org/a/kap/iaecre/v4y1998i3p229-24210.1007-bf02294892.html
   My bibliography  Save this article

A new approach in multivariate time series specification

Author

Listed:
  • Celina Pestano
  • Concepción González

Abstract

Within the study of multivariate time series, this work is centered on vector autoregressive moving average (VARMA) models, specifically on the specification stage. Until now, numerous procedures have been proposed to resolve the problem of identifying the dynamic behavior in a VARMA model framework. A new strategy is added to specify VARMA models justified by results within the field of matrix Padé approximation. Besides contributing a characterization of these models, alternative methods are added to those already in the literature to deal with the problems of identifiability and exchangeability. The obtained characterizations have the advantage of graphically presenting the results in tables for direct interpretation. The proposed technique is illustrated by means of a theoretical example, a simulated model, and data from economic variables (already dealt with by other authors) in order to compare results. Copyright International Atlantic Economic Society 1998

Suggested Citation

  • Celina Pestano & Concepción González, 1998. "A new approach in multivariate time series specification," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 4(3), pages 229-242, August.
  • Handle: RePEc:kap:iaecre:v:4:y:1998:i:3:p:229-242:10.1007/bf02294892
    DOI: 10.1007/BF02294892
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/BF02294892
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/BF02294892?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lutkepohl, Helmut & Poskitt, D S, 1996. "Specification of Echelon-Form VARMA Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 69-79, January.
    2. Tsay, Ruey S, 1989. "Parsimonious Parameterization of Vector Autoregressive Moving Average Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(3), pages 327-341, July.
    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. DUFOUR, Jean-Marie & TAREK, Jouini, 2005. "Asymptotic Distribution of a Simple Linear Estimator for VARMA Models in Echelon Form," Cahiers de recherche 2005-09, Universite de Montreal, Departement de sciences economiques.
    2. George Athanasopoulos & D. Poskitt & Farshid Vahid, 2012. "Two Canonical VARMA Forms: Scalar Component Models Vis-à-Vis the Echelon Form," Econometric Reviews, Taylor & Francis Journals, vol. 31(1), pages 60-83.
    3. Jean-Marie Dufour & Tarek Jouini, 2011. "Asymptotic Distributions for Some Quasi-Efficient Estimators in Echelon VARMA Models," CIRANO Working Papers 2011s-25, CIRANO.
    4. Bhansali, Rajendra J., 2020. "Model specification and selection for multivariate time series," Journal of Multivariate Analysis, Elsevier, vol. 175(C).
    5. Christian Kascha, 2012. "A Comparison of Estimation Methods for Vector Autoregressive Moving-Average Models," Econometric Reviews, Taylor & Francis Journals, vol. 31(3), pages 297-324.
    6. Holger Bartel & Helmut Lutkepohl, 1998. "Estimating the Kronecker indices of cointegrated echelon-form VARMA models," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages 76-99.
    7. Chan, Joshua C.C. & Eisenstat, Eric & Koop, Gary, 2016. "Large Bayesian VARMAs," Journal of Econometrics, Elsevier, vol. 192(2), pages 374-390.
    8. D.S. Poskitt, 2004. "Some Results on the Identification and Estimation of Vector ARMAX Processes," Monash Econometrics and Business Statistics Working Papers 12/04, Monash University, Department of Econometrics and Business Statistics.
    9. Melard, Guy & Roy, Roch & Saidi, Abdessamad, 2006. "Exact maximum likelihood estimation of structured or unit root multivariate time series models," Computational Statistics & Data Analysis, Elsevier, vol. 50(11), pages 2958-2986, July.
    10. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, October.
    11. Athanasopouolos, George & Poskitt, Don & Vahid, Farshid & Yao, Wenying, 2014. "Forecasting with EC-VARMA models," Working Papers 2014-07, University of Tasmania, Tasmanian School of Business and Economics, revised 22 Feb 2014.
    12. René Lalonde & Jennifer Page & Pierre St-Amant, 1998. "Une nouvelle méthode d'estimation de l'écart de production et son application aux États-Unis, au Canada et à l'Allemagne," Staff Working Papers 98-21, Bank of Canada.
    13. Casals, J. & García-Hiernaux, A. & Jerez, M., 2012. "From general state-space to VARMAX models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(5), pages 924-936.
    14. Alfredo García-Hiernaux, 2009. "Diagnostic checking using subspace methods," Documentos de Trabajo del ICAE 2009-03, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    15. Dias, Gustavo Fruet & Kapetanios, George, 2018. "Estimation and forecasting in vector autoregressive moving average models for rich datasets," Journal of Econometrics, Elsevier, vol. 202(1), pages 75-91.
    16. Helmut Luetkepohl, 2007. "Econometric Analysis with Vector Autoregressive Models," Economics Working Papers ECO2007/11, European University Institute.
    17. Dupasquier, Chantal & Guay, Alain & St-Amant, Pierre, 1999. "A Survey of Alternative Methodologies for Estimating Potential Output and the Output Gap," Journal of Macroeconomics, Elsevier, vol. 21(3), pages 577-595, July.
    18. Marie-Christine Duker & David S. Matteson & Ruey S. Tsay & Ines Wilms, 2024. "Vector AutoRegressive Moving Average Models: A Review," Papers 2406.19702, arXiv.org.
    19. Gil-Alana, Luis A. & Gupta, Rangan & Olubusoye, Olusanya E. & Yaya, OlaOluwa S., 2016. "Time series analysis of persistence in crude oil price volatility across bull and bear regimes," Energy, Elsevier, vol. 109(C), pages 29-37.
    20. Emre Kahraman & Gazanfer Unal, 2016. "Multiple Wavelet Coherency Analysis and Forecasting of Metal Prices," Papers 1602.01960, arXiv.org.

    More about this item

    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:kap:iaecre:v:4:y:1998:i:3:p:229-242:10.1007/bf02294892. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.