The Likelihood Function of Conditionally Heteroskedastic Factor Models
We derive the likelihood function and score of factor models with dynamic heteroskedasticity, and the Kuhn-Tucker conditions defining the inequality restricted maximum likelihood estimators that guarantee a positive definite convariance matrix. We present three methods to compute the likelihood function, its gradient and factor scores, which are numerically efficient and reliable, and statistically sound. We show that the incidence of zero idiosyncratic variance estimates (Heywood cases) depends on the correlation of a variable with the rest.
Year of publication: |
2000
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Authors: | SENTANA, Enrique |
Published in: |
Annales d'Economie et de Statistique. - École Nationale de la Statistique et de l'Admnistration Économique (ENSAE). - 2000, 58, p. 1-19
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Publisher: |
École Nationale de la Statistique et de l'Admnistration Économique (ENSAE) |
Saved in:
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