Advertisement

Multivariate Structural Models

  • Víctor Gómez
Chapter
Part of the Statistics and Computing book series (SCO)

Abstract

Multivariate structural models are defined in a way similar to that of univariate structural models, described in Sect.  4.1. For example, let the stochastic vector Yt satisfy Yt = Pt + St + It, where Pt is the trend, St is the seasonal, and It is the irregular component.

References

  1. Akaike, H. (1974). Markovian representation of stochastic processes and its application to the analysis of autoregressive moving average processes. Annals of the Institute of Statistical Mathematics,26, 363–387.MathSciNetCrossRefGoogle Scholar
  2. Cleveland, W. P., & Tiao, G. C. (1976). Decomposition of seasonal time series: A model for the X-11 program. Journal of the American Statistical Association,71, 581–587.MathSciNetCrossRefGoogle Scholar
  3. Creal, D., Koopman, S. J., & Zivot, E. (2010). Extracting a robust US business cycle using a time–varying multivariate model–based bandpass filter. Journal of Applied Econometrics,25, 695–719.MathSciNetCrossRefGoogle Scholar
  4. Doménech, R., & Gómez, V. (2006). Estimating potential output, core inflation, and the NAIRU as latent variables. Journal of Business and Economic Statistics,24, 354–365.MathSciNetCrossRefGoogle Scholar
  5. Gómez, V. (2001). The use of butterworth filters for trend and cycle estimation in economic time series. Journal of Business and Economic Statistics,19, 365–373.MathSciNetCrossRefGoogle Scholar
  6. Gómez, V. (2016). Multivariate time series models with linear state space structure. New York: Springer.zbMATHGoogle Scholar
  7. Gómez, V., & Aparicio-Pérez, F. (2009). A new state-space methodology to disaggregate multivariate time series. Journal of Time Series Analysis,30, 97–124.MathSciNetCrossRefGoogle Scholar
  8. Gómez, V., & Maravall, A. (1994). Estimation, prediction, and interpolation for nonstationary series with the Kalman filter. Journal of the American Statistical Association,89, 611–624.MathSciNetzbMATHGoogle Scholar
  9. Gómez, V., & Maravall, A. (2001). Programs TRAMO and SEATS, instructions for the user (Beta Version: June 1997) (Working Paper No. 97001). Dirección General De Presupuestos, Ministry of Finance, Madrid, Spain.Google Scholar
  10. Harvey, A. C. (1989). Forecasting, structural time series models and the Kalman filter. Cambridge: Cambridge University Press.Google Scholar
  11. Mariano, R. S., & Murasawa, Y. (2003). A new coincident index of business cycles based on monthly and quarterly series. Journal of Applied Econometrics,18, 427–443.CrossRefGoogle Scholar
  12. Valle e Azevedo, J., Koopman, S. J., & Rua, A. (2006). Tracking the business cycle of the euro area: A multivariate model–based bandpass filter. Journal of Business and Economic Statistics,24, 278–290.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Víctor Gómez
    • 1
  1. 1.General Directorate of BudgetsMinistry of Finance and Public AdministrationsMadridSpain

Personalised recommendations