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 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.
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Bibliographic InfoPaper provided by Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie) in its series Working Papers. Serie AD with number 1997-22.
Length: 48 pages
Date of creation: Oct 1997
Date of revision:
Publication status: Published by Ivie
Factor Models; Conditional Heteroskedasticity; Identification;
Other versions of this item:
- Sentana, Enrique & Fiorentini, Gabriele, 2001. "Identification, estimation and testing of conditionally heteroskedastic factor models," Journal of Econometrics, Elsevier, vol. 102(2), pages 143-164, June.
- 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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