Identification, estimation and testing of conditionally heteroskedastic factor models
AbstractWe 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 does not rely on knowledge of any factor estimates, and explain how to compute correct standard errors.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Econometrics.
Volume (Year): 102 (2001)
Issue (Month): 2 (June)
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Web page: http://www.elsevier.com/locate/jeconom
Other versions of this item:
- 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).
- Sentana, E. & Fiorentini, G., 1997. "Identification, Estimation and Testing of Conditionally Heteroskedastic Factor Model," Papers 9709, Centro de Estudios Monetarios Y Financieros-.
- 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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