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Robust Standard Errors in Small Samples: Some Practical Advice

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  • Guido W. Imbens
  • Michal Kolesar

Abstract

In this paper we discuss the properties of confidence intervals for regression parameters based on robust standard errors. We discuss the motivation for a modification suggested by Bell and McCaffrey (2002) to improve the finite sample properties of the confidence intervals based on the conventional robust standard errors. We show that the Bell-McCaffrey modification is the natural extension of a principled approach to the Behrens-Fisher problem, and suggest a further improvement for the case with clustering. We show that these standard errors can lead to substantial improvements in coverage rates even for sample sizes of fifty and more. We recommend researchers calculate the Bell-McCaffrey degrees-of-freedom adjustment to assess potential problems with conventional robust standard errors and use the modification as a matter of routine.

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  • Guido W. Imbens & Michal Kolesar, 2012. "Robust Standard Errors in Small Samples: Some Practical Advice," NBER Working Papers 18478, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:18478
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    References listed on IDEAS

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    1. James H. Stock & Mark W. Watson, 2008. "Heteroskedasticity-Robust Standard Errors for Fixed Effects Panel Data Regression," Econometrica, Econometric Society, vol. 76(1), pages 155-174, January.
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    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

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