A re-tweet from a colleague whom I follow on Twitter brought an important paper to my attention. I thought I’d share it more widely.
You can tell right away, from its title, that this paper is going to be a must-read for empirical economists. And note the words, “Small-sample” in the title – that sounds interesting.
Here’s a compilation of Beth’s six tweets:
“Econ friends, @jepusto and I have a new paper out that we would love to share. It’s about clustering your standard errors (more below).
Any suggestions for how to get these methods out to economists given that we aren’t NBER?
Summary: Our paper provides small-sample adjustments to cluster robust variance estimation (CRVE). It can be used with panel data, experimental data, and regression. You can implement the method in a Stata macro called REG_SANDWICH and an R package called clubSandwich.
Why do you need this? Regular CRVE doesn’t do so well, even with as many as 100 clusters (!). In fact, CRVE only gives you appropriate Type I error when your covariates are balanced.
What did we do? We extended the bias-robust linearization method (BRL) by Bell & McCaffrey in three ways: (1) in addition to a t-test, there is now an F-test; (2) We can handle the inclusion of fixed effects; (3) You get the same results whether you use FE or absorption.
How does it work? The adjustment inflates the standard errors a small bit. But more importantly, it provides Satterthwaite-type degrees of freedom that are more appropriate. The result is a test we call the ‘Approximate Hotelling’s T-squared’ (AHT) test.
We’d love to share the work broadly, so if you have ideas, please let us know. Thanks!”
I’ve added the links to the R and Stata software in the quote above.
There are also some nice R vignettes available:
Well, Beth, who can resist a club sandwich? I don’t know if this post will help you and James, but I do hope so.
These new results, and the associated software certainly deserve to be publicized, and used, widely.
Check them out!
(Disclaimer: I do not know either James of Beth, personally or professionally.)
© 2018, David E. Giles
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