Cited by 499Advanced Statistical Methods and ModelsStatistical Methods and Bayesian InferenceStatistical and numerical algorithms

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On The So-Called “Huber Sandwich Estimator” and “Robust Standard Errors”

Freedman, David A·2006·The American Statistician

DOI 10.1198/000313006x152207

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Abstract

The “Huber Sandwich Estimator” can be used to estimate the variance of the MLE when the underlying model is incorrect. If the model is nearly correct, so are the usual standard errors, and robustification is unlikely to help much. On the other hand, if the model is seriously in error, the sandwich may help on the variance side, but the parameters being estimated by the MLE are likely to be meaningless—except perhaps as descriptive statistics.

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Authors: Freedman, D. A.
Affiliations: University of California, Berkeley (US)
Corresponding author: Freedman, David A
Venue: The American Statistician
Publisher: Informa UK Limited
Published: 2006-11
Volume: 60
Issue: 4
Pages: 299-302
ISSN: 0003-1305 (ISSN-L)
1537-2731
DOI: 10.1198/000313006x152207
OpenAlex: W2018502278
Cited by: 498
References: 19
Citations by year: 2026: 33 · 2025: 34 · 2024: 40 · 2023: 41 · 2022: 27 · 2021: 43 · 2020: 34 · 2019: 20 · 2018: 49 · 2017: 17 · 2016: 23 · 2015: 31 · 2014: 27 · 2013: 19 · 2012: 17
FWCI: 7.20
Type: journal article
Language: en
Open access: closed
Locations: The American Statistician (publishedVersion)
RePEc: Research Papers in Economics (submittedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Physical Sciences › Mathematics › Applied Mathematics › Statistical and numerical algorithms
Keywords: robust standard errors, model misspecification, maximum likelihood estimation, variance estimation, heteroscedasticity

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On The So-Called “Huber Sandwich Estimator” and “Robust Standard Errors”

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