Hi
You don't mention whether your data is a cross-section or a panel. That's
quite important.
Regarding (1) you have clusters of firms, so you can estimate your variance
matrix using the option cluster. Cochrane-Orcutt works for time
autocorrelation, so you need a measure of "proximity"among the firms within
a cluster. I think you don't have that. In time-series, that measure is
given by the time dimension.
Regarding (2), I think you need to think carefully about the relationship
among your equations. Are you estimating structural or reduced forms
equations? For instance, is accounting performance included as a regressor
in your stock-market valuation?. If it is you have a simultaneous equation
model. If it's not, you're estimating a reduced form, but you have to be
very careful about the interpretation of your marginal effects.
I hope it helps
Benjamin
-----Mensaje original-----
De: [email protected]
[mailto:[email protected]] En nombre de Dalhia Mani
Enviado el: Saturday, October 04, 2008 4:48 PM
Para: [email protected]
Asunto: st: SUR correction for autocorrelation
hi,
I have a set of equations that specify the relationship between a set
of independent variables and outcome variables - survival, stockmarket
and accounting performance. I have two questions that I would
appreciate your help with.
1) The data is at the firm level. Some of the firms belong to
clusters of firms, and hence I expect autocorrelation in the residuals
when I run each equation separately. Therefore, I plan to use the the
Prais-Winston command, specifying the Cochran-Orcutt option in stata
to correct for autocorrelation when running each equation separately.
I think this approach is correct, however I am not a 100% sure, and
will appreciate it if you think otherwise and can correct me.
2) I also need to use a simultaneous unrelated regression (SUR) model
since it is possible that the set of equations are related (e.g.
survival might be related to performance). How do I correct for
autocorrelation for the SUR model in stata?
Any suggestions and advice will be much appreciated.
thanks
dalhia
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