I have a question about the ``cluster'' option (common to many
commands, but I am invoking it from the simple ``reg'' command).
In a model where every individual i is also a part of a group j, and
the dependent variable is determined by characteristics not only of the
individual i but also of the group j, it seems like a regression ought
to attempt to fit the model
y_i = x_i b + w_j g + e_i + u_j
where x_i are individual characteristics, w_j are group
characteristics, e_i is an individual error term, and u_j is a group
error term. Can anyone help me contrast an error component model like
this (fitted either through f-GLS or ML) with what ``cluster'' does? I
have already read William Rogers' article ``Regression standard errors
in clustered samples'', but am still unclear.
Thank you very much if anyone has any pointers on this.
