Robust Standard Errors in Small Samples: Some Practical Advice

30 Pages Posted: 20 Oct 2012  

Guido W. Imbens

Stanford Graduate School of Business

Michal Kolesár

Princeton University

Date Written: October 2012

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.

Suggested Citation

Imbens, Guido W. and Kolesár, Michal, Robust Standard Errors in Small Samples: Some Practical Advice (October 2012). NBER Working Paper No. w18478. Available at SSRN: https://ssrn.com/abstract=2164602

Guido W. Imbens (Contact Author)

Stanford Graduate School of Business ( email )

655 Knight Way
Stanford, CA 94305-5015
United States

Michal Kolesar

Princeton University ( email )

22 Chambers Street
Princeton, NJ 08544
United States

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