More efficient tests robust to heteroskedasticity of unknown form

Emmanuel Flachaire

Post-Print from HAL

Abstract: In the presence of heteroskedasticity of unknown form, the Ordinary Least Squares parameter estimator becomes inefficient and its covariance matrix estimator inconsistent. Eicker (1963) and White (1980) were the first to propose a robust consistent covariance matrix estimator, that permits asymptotically correct inference. This estimator is widely used in practice. % Cragg (1983) proposed a more efficient estimator, but concluded thattests based on it are unreliable. Thus, this last estimator has not been used in practice. This paper is concerned with finite sample properties of tests robust to heteroskedasticity of unknown form. Our results suggestthat reliable and more efficient tests can be obtained with the Cragg estimators in small samples.

Keywords: wild bootstrap; heteroskedasticity-robust test; regression model (search for similar items in EconPapers)
Date: 2005
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00175914
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

Published in Econometric Reviews, 2005, 24 (2), pp.219-241. ⟨10.1081/ETC-200067942⟩

Downloads: (external link)
https://shs.hal.science/halshs-00175914/document (application/pdf)

Related works:
Working Paper: More efficient tests robust to heteroskedasticity of unknown form (2005)
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: https://EconPapers.repec.org/RePEc:hal:journl:halshs-00175914

DOI: 10.1081/ETC-200067942

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().