Using standard errors as taught to undergraduates can lead to incorrect inference if information is replicated in some way, such as applying GDP statistics to household-level data. Stata's useful cluster option is a common method of addressing this issue.
As much of the work produced by the Geary Institute is microeconometric in nature, researchers may be interested in two recent papers on the topic.
Andrew Gelman cites a paper that suggests cluster'ing is inadequate and that multi-level modelling should be preferred, while Barrios, Diamond, Imbens and Kolesar (2010) suggest researchers should also be wary of spatial correlations.
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Multi-level modelling is more accessible now, well if you are a Stata user anyway. Previously you might have needed to use dedicated software (ML3Win was one I think) or maybe R but now one can do quite a bit in Stata: check out the "mixed effects" models. Another thing one has no excuse for not doing...
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