IDEAS home Printed from https://ideas.repec.org/a/bla/jtsera/v16y1995i4p431-444.html

Estimation Of The Multivariate Autoregressive Moving Average Having Parameter Restrictions And An Application To Rotational Sampling

Author

Listed:
  • Dong Wan Shin
  • Sahadeb Sarkar

Abstract

. The vector autoregressive moving average model with nonlinear parametric restrictions is considered. A simple and easy‐to‐compute Newton‐Raphson estimator is proposed that approximates the restricted maximum likelihood estimator which takes full advantage of the information contained in the restrictions. In the case when there are no parametric restrictions, our Newton‐Raphson estimator is equivalent to the estimator proposed by Reinsel et al. (Maximum likelihood estimators in the multivariate autoregressive moving‐average model from a generalized least squares view point. J. Time Ser. Anal. 13 (1992), 133–45). The Newton‐Raphson estimation procedure also extends to the vector ARMAX model. Application of our Newton‐Raphson estimation method in rotational sampling problems is discussed. Simulation results are presented for two different restricted models to illustrate the estimation procedure and compare its performance with that of two alternative procedures that ignore the parametric restrictions.

Suggested Citation

  • Dong Wan Shin & Sahadeb Sarkar, 1995. "Estimation Of The Multivariate Autoregressive Moving Average Having Parameter Restrictions And An Application To Rotational Sampling," Journal of Time Series Analysis, Wiley Blackwell, vol. 16(4), pages 431-444, July.
    • Handle: RePEc:bla:jtsera:v:16:y:1995:i:4:p:431-444
    DOI: 10.1111/j.1467-9892.1995.tb00244.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-9892.1995.tb00244.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1467-9892.1995.tb00244.x?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
    ---><---

    References listed on IDEAS

    as
    1. Dong Wan Shin, 1993. "Maximum Likelihood Estimation For Autoregressive Processes Disturbed By A Moving Average," Journal of Time Series Analysis, Wiley Blackwell, vol. 14(6), pages 629-643, November.
    2. Sergio Koreisha & Tarmo Pukkila, 1989. "Fast Linear Estimation Methods For Vector Autoregressive Moving‐Average Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 10(4), pages 325-339, July.
    3. Marc Hallin, 1984. "Spectral factorization of nonstationary moving average processes," ULB Institutional Repository 2013/2001, ULB -- Universite Libre de Bruxelles.
    4. Zellner, Arnold & Palm, Franz, 1974. "Time series analysis and simultaneous equation econometric models," Journal of Econometrics, Elsevier, vol. 2(1), pages 17-54, May.
    5. Reinsel, Greg, 1979. "FIML estimation of the dynamic simultaneous equations model with ARMA disturbances," Journal of Econometrics, Elsevier, vol. 9(3), pages 263-281, February.
    6. Gwilym M. Jenkins & Athar S. Alavi, 1981. "Some Aspects Of Modelling And Forecasting Multivariate Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 2(1), pages 1-47, January.
    7. Kohn, R, 1979. "Asymptotic Estimation and Hypothesis Testing Results for Vector Linear Time Series Models," Econometrica, Econometric Society, vol. 47(4), pages 1005-1030, July.
    8. Gregory C. Reinsel & Sabyasachi Basu & Sook Fwe Yap, 1992. "Maximum Likelihood Estimators In The Multivariate Autoregressive Moving‐Average Model From A Generalized Least Squares Viewpoint," Journal of Time Series Analysis, Wiley Blackwell, vol. 13(2), pages 133-145, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Stefano F. Tonellato, 2005. "Identifiability Conditions for Spatio-Temporal Bayesian Dynamic Linear Models," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 81-101.

    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. Marie-Christine Duker & David S. Matteson & Ruey S. Tsay & Ines Wilms, 2024. "Vector AutoRegressive Moving Average Models: A Review," Papers 2406.19702, arXiv.org.
    2. D. S. Poskitt & M. O. Salau, 1995. "On The Relationship Between Generalized Least Squares And Gaussian Estimation Of Vector Arma Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 16(6), pages 617-645, November.
    3. Alfredo García-Hiernaux & José Casals & Miguel Jerez, 2012. "Estimating the system order by subspace methods," Computational Statistics, Springer, vol. 27(3), pages 411-425, September.
    4. Rafael Flores de Frutos, 1993. "Sobre la Estimación de Primas por Plazo dentro de la Estructura Temporal de Tipos de Interes," Documentos de Trabajo del ICAE 9302, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    5. Emre Kahraman & Gazanfer Unal, 2016. "Multiple Wavelet Coherency Analysis and Forecasting of Metal Prices," Papers 1602.01960, arXiv.org.
    6. Rafael Flors de Frutos & Alfredo M. Pereira, 1993. "Testing theories of economic fluctuations and growth in early development. (The case of the Chesapeake tobacco economy)," Documentos de Trabajo del ICAE 9308, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    7. 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.
    8. Jean-Marie Dufour & Tarek Jouini, 2011. "Asymptotic Distributions for Some Quasi-Efficient Estimators in Echelon VARMA Models," CIRANO Working Papers 2011s-25, CIRANO.
    9. Francesca Di Iorio & Umberto Triacca, 2022. "A comparison between VAR processes jointly modeling GDP and Unemployment rate in France and Germany," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(3), pages 617-635, September.
    10. John McDonald & Houston Stokes, 2013. "Monetary Policy and the Housing Bubble," The Journal of Real Estate Finance and Economics, Springer, vol. 46(3), pages 437-451, April.
    11. Anna Mikusheva & Mikkel Sølvsten, 2025. "Linear regression with weak exogeneity," Quantitative Economics, Econometric Society, vol. 16(2), pages 367-403, May.
    12. Bolkesjø, Torjus F. & Buongiorno, Joseph, 2006. "Short- and long-run exchange rate effects on forest product trade: Evidence from panel data," Journal of Forest Economics, Elsevier, vol. 11(4), pages 205-221, January.
    13. Umberto Triacca, 2016. "Measuring the Distance between Sets of ARMA Models," Econometrics, MDPI, vol. 4(3), pages 1-11, July.
    14. McNulty, Mark S., 1985. "Information usage in the formation of price expectations: theory and econometric tests," ISU General Staff Papers 1985010108000013085, Iowa State University, Department of Economics.
    15. McKenzie, C.R., 1997. "The properties of some two step estimators of ARMA Models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 43(3), pages 451-456.
    16. Nguyen, Giang & Engle, Robert & Fleming, Michael & Ghysels, Eric, 2020. "Liquidity and volatility in the U.S. Treasury market," Journal of Econometrics, Elsevier, vol. 217(2), pages 207-229.
    17. Palm, F.C., 1981. "Structural econometric modelling and time series analysis towards an integrated approach," Serie Research Memoranda 0004, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    18. Cubadda, Gianluca & Hecq, Alain & Palm, Franz C., 2009. "Studying co-movements in large multivariate data prior to multivariate modelling," Journal of Econometrics, Elsevier, vol. 148(1), pages 25-35, January.
    19. Gupta, Rangan & Kabundi, Alain & Miller, Stephen M., 2011. "Forecasting the US real house price index: Structural and non-structural models with and without fundamentals," Economic Modelling, Elsevier, vol. 28(4), pages 2013-2021, July.

    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:bla:jtsera:v:16:y:1995:i:4:p:431-444. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782 .

    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.