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Heteroskedastic Dynamic Factor Models: A Monte Carlo Study

Author

Listed:
  • Gijsbert Suren

    (VU University, Amsterdam)

  • Guilherme Moura

    (Federal University of Santa Catarina)

Abstract

We propose to estimate heteroskedastic dynamic factor models using the Kalman filter, where the state vector is augmented with the heteroskedastic disturbances. Although this model is not conditionally Gaussian, Monte Carlo results show that parameters can be accurately estimated.

Suggested Citation

  • Gijsbert Suren & Guilherme Moura, 2012. "Heteroskedastic Dynamic Factor Models: A Monte Carlo Study," Economics Bulletin, AccessEcon, vol. 32(4), pages 2884-2898.
    • Handle: RePEc:ebl:ecbull:eb-12-00269
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    References listed on IDEAS

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    More about this item

    Keywords

    state space models; dynamic factor models; GARCH; Monte Carlo simulations;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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