Working Paper: NBER ID: w18478
Authors: 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.
Keywords: No keywords provided
JEL Codes: C01
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Conventional robust standard errors (EH) (C51) | biased downward in small samples (C46) |
| Liang-Zeger (LZ) variance estimators (C21) | biased downward in small samples (C46) |
| BM degrees of freedom adjustment (C51) | differs significantly from traditional methods (C60) |
| Clustering modifications to BM procedure (C38) | enhance performance of confidence intervals in clustered data settings (C38) |
| Bell-McCaffrey (BM) adjustment (C51) | substantial improvements in coverage rates (I13) |
| BM adjustment (C59) | improved coverage rates for sample sizes of fifty or more (C83) |