Economics at your fingertips  

A Minimax Bias Estimator for OLS Variances under Heteroskedasticity

Mumtaz Ahmed () and Asad Zaman ()

MPRA Paper from University Library of Munich, Germany

Abstract: Analytic evaluation of heteroskedasticity consistent covariance matrix estimates (HCCME) is difficult because of the complexity of the formulae currently available. We obtain new analytic formulae for the bias of a class of estimators of the covariance matrix of OLS in a standard linear regression model. These formulae provide substantial insight into the properties and performance characteristics of these estimators. In particular, we find a new estimator which minimizes the maximum possible bias and improves substantially on the standard Eicker-White estimate.

Keywords: Eicker-White; OLS; Bias; Worst Case Bias (search for similar items in EconPapers)
JEL-codes: C1 C2 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().

Page updated 2019-01-27
Handle: RePEc:pra:mprapa:55724