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Re: st: Panel SUR with Unbalanced Observations
From
Stephen O Neill <[email protected]>
To
[email protected]
Subject
Re: st: Panel SUR with Unbalanced Observations
Date
Mon, 25 Oct 2010 03:18:55 -0700 (PDT)
Hi Statalist,
I too would like to run SUR on an unbalanced panel and would gretaly appreciate
a code that deos this!
Stephen
----- Original Message ----
From: Chris Parker <[email protected]>
To: [email protected]
Sent: Mon, October 25, 2010 8:23:08 AM
Subject: st: Panel SUR with Unbalanced Observations
Hi statalist,
I have quarterly data on 24 brokers for two exchanges over a span of
5.5 years. I am trying to explain the allocation of the brokers orders
by a number of other variables. The regression I would like to run is
as an SUR with two equations, one for each exchange. However I run
into two problems. First one exchange opened after another so the
equations do not have the same number of observations. I attempted to
solve this problem using advice from Allen McDowell:
http://www.stata-journal.com/sjpdf.html?articlenum=st0079 This is
where I enter the second problem which is that I have multiple
brokers. The final step before running xtgee requires a tsset which I
cannot do because I have multiple observations per time period
corresponding to the different brokers. I think I need to wide my data
so that in each exchange-time observation I have all of the
independent and dependent variables. However I am not sure if this is
what needs to be done. Any help understanding this process would be
greatly appreciated.
Additionally, I noticed a message from Kit Baum in previous posts that
I think is what I need.
http://www.stata.com/statalist/archive/2007-11/msg00346.html Kit, do
you still have this stata code available? I would really appreciate a
copy if possible.
Does anyone else have an idea on how to run this regression?
Chris
Chris Parker
________________________________
PhD Candidate | Management Science & Operations
London Business School | Regent's Park | London NW1 4SA | United Kingdom
Direct line +44 (0)20 7000 8816 | Email [email protected]
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