Robust Standard Errors in Small Samples: Some Practical Advice
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.
Financial support for this research was generously provided through NSF grant 0820361. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
Guido W. Imbens & Michal Kolesár, 2016. "Robust Standard Errors in Small Samples: Some Practical Advice," Review of Economics and Statistics, vol 98(4), pages 701-712. citation courtesy of