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A New Heteroskedastic Consistent Covariance Matrix Estimator using Deviance Measure

Author(s)
Nuzhat Aftab College of Statistical and Actuarial Sciences University of the Punjab,Quaid-i-Azam Campus Lahore,Pakistan.
Sohail Chand College of Statistical and Actuarial Sciences University of the Punjab, Quaid-i-Azam Campus Lahore, Pakistan
Abstract
In this article, we propose a new heteroskedastic consistent covariance matrix estimator, HC6, which is based on deviance measure. We have studied the finite sample behavior of the test statistic based on this new HC estimator. We compare its performance with other HC estimators namely HC1, HC3 and HC4m, which are also used in case of leverage observations. Extensive simulation studies are used to study the effect of various levels of heteroskedasticity on the performance of the quasi tests based on HC estimators. Results showed that the test statistic based on new suggested estimator has better asymptotic approximation and have less size distortion in small samples especially when high level heteroskedasticity is present in the data. 
Publication Details
Page(s) 235-244
DOI DOI not available
Published Journal: Pakistan Journal of Statistics and Operation Research, Volume: 12, Issue: 2, Year: 2016

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Keywords
Regression, Heteroskedasticity, Covariance matrix estimation, Deviance, Influential points
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