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Estimating the system order by subspace methods

Author

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  • Alfredo García-Hiernaux
  • José Casals
  • Miguel Jerez

Abstract

This paper discusses how to specify the order of a state-space model. To do so, we start by revising existing approaches and find in them two basic shortcomings: (i) some of them have a poor performance in short samples and (ii) most of them are not robust, meaning that their performance critically depends on the data generating process. We tackle these two issues by proposing new and refined criteria. Monte Carlo simulations provide evidence of the potential of the proposals. Copyright Springer-Verlag 2012

Suggested Citation

  • 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.
    • Handle: RePEc:spr:compst:v:27:y:2012:i:3:p:411-425
    DOI: 10.1007/s00180-011-0264-2
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    References listed on IDEAS

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    1. 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.
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    3. Jesús Gonzalo & Jean‐Yves Pitarakis, 2002. "Lag length estimation in large dimensional systems," Journal of Time Series Analysis, Wiley Blackwell, vol. 23(4), pages 401-423, July.
    4. Carl Eckart & Gale Young, 1936. "The approximation of one matrix by another of lower rank," Psychometrika, Springer;The Psychometric Society, vol. 1(3), pages 211-218, September.
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    6. Casals, Jose & Sotoca, Sonia & Jerez, Miguel, 1999. "A fast and stable method to compute the likelihood of time invariant state-space models," Economics Letters, Elsevier, vol. 65(3), pages 329-337, December.
    7. Ruey S. Tsay, 1989. "Identifying Multivariate Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 10(4), pages 357-372, July.
    8. Bujosa, Marcos & Garcia-Ferrer, Antonio & Young, Peter C., 2007. "Linear dynamic harmonic regression," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 999-1024, October.
    9. Bauer, Dietmar, 2005. "Estimating Linear Dynamical Systems Using Subspace Methods," Econometric Theory, Cambridge University Press, vol. 21(1), pages 181-211, February.
    10. Bengtsson, Thomas & Cavanaugh, Joseph E., 2006. "An improved Akaike information criterion for state-space model selection," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2635-2654, June.
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    Cited by:

    1. Brum-Civelli, Conrado & Garcia-Hiernaux, Alfredo, 2023. "An indicator of monetary bias for emerging and partially dollarized economies: The case of Uruguay," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 206-219.
    2. Rodrigo Mulero & Alfredo Garcia-Hiernaux, 2023. "Forecasting unemployment with Google Trends: age, gender and digital divide," Empirical Economics, Springer, vol. 65(2), pages 587-605, August.

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    More about this item

    Keywords

    Information criteria; State-space models; Subspace methods; System order; C32; C51; C52;
    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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