The Likelihood Function of Conditionally Heteroskedastic Factor Models
Enrique Sentana ()
Annals of Economics and Statistics, 2000, issue 58, 1-19
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.
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Persistent link: https://EconPapers.repec.org/RePEc:adr:anecst:y:2000:i:58:p:1-19
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