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you could use the cluster estimator with the areg option if you have a full 
set of dummy variables corresponding to the clusters'id. The command works, 
but the FAQ, warns you about the rank of the covariance matrix, which is k, 
the number of parameters estimated not including the constant or the fixed 
effects. Does this mean that to increase the rank you should have more 
parameters beside the dummies? This seems counterintuitive to me.

Other issues of concern are:

-Why, if I use the cluster option with reg, including manually a full set of 
dummy variables, the F test on the coefficients is not reported on the basis 
that the rank of the VCE is too small whilst  the areg command reports it?

-Why the NL command with the cluster option behaves like areg and not like 

-More generally, I found some papers Kezdi(2003),Bertrand et al(2002), cited 
in Wooldridge: 

that seem to warrant the use of the cluster option even when N, is not 
particularly big with respect to T, as far as it has reasonable size. 
Kezdi(2003), performs his simulations demeaning the variables instead of 
including dummies. I suspect (probably erroneously) that there is a 
computational convenience behind his choice that may have to deal with the 
problem of degree of freedoms in the VCE (not considering the algebraic 
equivalence of the two methods). Thanks for any insight you may be able to 
give me about the topic

Have a good day,


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