Abstract
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 gua- rantee a positive definite covariance 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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
