Zelig for Clustered Standard Errors

In regression modeling, it is common to correct standard errors for natural groupings (clusters) in the data.  There are various ways to calculate these values using R, from doing it manually to using one of many packages.

Theoretically, Zelig is an R package that will cluster standard errors automatically.  In my experience, however, it does not actually do so.  Instead, the results for a linear model and a linear model with clustered robust standard errors are the same.  (I am in a rush and so do not have time to post regression results, but you can do it and see the same problem.)  I have had the same experience with negative binomial models, and this person has had the same issue with logit models.  In other words, Zelig seems to have a systematic bug which prevents it from (properly?) calculating robust clustered standard errors.  Or, if there is no bug, the documentation’s description for calculating them is misleading.

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