Heteroskedasticity-Robust Inference in Finite Samples
Jerry Hausman and
Christopher J. Palmer
No 17698, NBER Working Papers from National Bureau of Economic Research, Inc
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 expansions of the test statistic distribution. Our preferred test outperforms existing methods in both size and power for low, moderate, and severe levels of heteroskedasticity.
JEL-codes: C01 C12 (search for similar items in EconPapers)
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Published as Economics Letters, Volume 116, Issue 2, August 2012, Pages 232-235
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Journal Article: Heteroskedasticity-robust inference in finite samples (2012)
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