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Identification, estimation and testing of conditionally heteroskedastic factor models

Author

Listed:
  • Gabriele Fiorentini

    (Universidad de Alicante)

  • Enrique Sentana Iváñez

    (CEMFI)

Abstract

We investigate several important inference issues for factor models with dynamic heteroskedasticity in the common factors. First, we show that such models are identified if we take into account the time-variation in the variances of the factors. Our results also apply to dynamic versions of the APT, dynamic factor models, and vector autoregressions.Secondly, we propose a consistent two-step estimation procedure which do es not rely on knowledge of any factor estimates, and explain how to compute correct standard errors.Thirdly, we develop a simple preliminary LM test for the presence of ARCH effects in the common factors. Finally, we conduct a Monte CarIo analysis of the finite sample properties of the proposed estimators and hypothesis tests.

Suggested Citation

  • Gabriele Fiorentini & Enrique Sentana Iváñez, 1997. "Identification, estimation and testing of conditionally heteroskedastic factor models," Working Papers. Serie AD 1997-22, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    • Handle: RePEc:ivi:wpasad:1997-22
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    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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