Heteroskedasticity-robust inference in finite samples
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Hausman_Heteroskedasticity-Robust.pdf
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Author(s)
Palmer, Christopher
Hausman, Jerry A.
Date Issued
February 2012
Journal
Economics Letters
Publisher
Elsevier
Citation
Hausman, Jerry, and Christopher Palmer. “Heteroskedasticity-Robust Inference in Finite Samples.” Economics Letters 116, no. 2 (August 2012): 232–235.
Version
Author's final manuscript
Abstract
Since the advent of heteroskedasticity-robust standard errors, several papers have proposed adjustments to the original White formulation. We replicate earlier findings that each of these adjusted estimators performs quite poorly in finite samples. We propose a class of alternative heteroskedasticity-robust tests of linear hypotheses based on an Edgeworth expansion of the test statistic distribution. Our preferred test outperforms existing methods in both size and power for low, moderate, and severe levels of heteroskedasticity.
MIT Department
Massachusetts Institute of Technology. Department of Economics
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Creative Commons Attribution-Noncommercial-NoDerivatives
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DOI of Published Version
https://doi.org/10.1016/j.econlet.2012.02.007
