Abstract
This paper presents a number of heteroskedasticity ridge consistent covariance matrix (HRCCM) estimators in order to develop a new version of mean square error criterion (denoted by HMSE) for comparing biased estimators in the presence of both collinearity and heteroskedasticity of unknown form. New methods to choose k (designated by k*) are also proposed and examined via Monte Carlo simulations (1000 replications). The Monte Carlo results reveal superiority of the estimator \(\widehat{\alpha }_{\rm GRR} \left( {{k}_{\rm mgh}^\ast } \right)\) over some well-known biased estimators by means of trace (HMSE) criterion when values of a number of factors that may affect their properties have been varied.
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.
