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Re: st: Panel data opinion wanted


From   "Mark Schaffer" <M.E.Schaffer@hw.ac.uk>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Panel data opinion wanted
Date   Thu, 25 Aug 2005 17:02:16 +0100 (BST)

This sounds really useful.  I would vote for "long" and the ability to
handle unbalanced panels.  I can't remember the last time I had a balanced
panel to work with.

--Mark

> Fellow listers,
>
> I am writing a procedure for Pooled Mean Group estimation for
> heterogeneous panels (a la Pesaran, Smith, and Shin). I have all the
> estimation figured out, but I would like some input regarding user
> preferences of model setup.
>
> Basically, I am interested to know if potential users of such a procedure
> prefer "long" or "wide" data format for this type of estimation.
>
> The give and take:
>
> Option 1: "Long" data: the procedure would seem much more like Stata's
> other xt estimation commands. More importantly, unbalanced panels can be
> easily handled. However, cross equation restrictions will be unavailable
> to the user.
>
> Option 2: "Wide" data: it will be trivial to allow users to impose cross
> equation (that is, cross panel) restrictions of parameter estimates.
> However, unbalanced panels will not be allowed.
>
> Please note that with either option the user will be able to perform
> cross-equation tests -- but only with Option 2 will the a priori
> restrictions be easily handled.
>
> My underlying question is which is more valuable to users: the ability to
> handle unbalanced panels or (in the context of these heterogeneous models)
> allow for cross-panel restrictions?
>
> I have my preference, but I would be interested to hear from any
> enlightened and opinionated users!
>
> Edward F. Blackburne III, PhD
> Associate Professor
> Economics and International Business
> Sam Houston State University
> blackburne@shsu.edu
> 936-294-3934
> *
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>


Prof. Mark Schaffer
Director, CERT
Department of Economics
School of Management & Languages
Heriot-Watt University, Edinburgh EH14 4AS
tel +44-131-451-3494 / fax +44-131-451-3294
email: m.e.schaffer@hw.ac.uk
web: http://www.sml.hw.ac.uk/ecomes



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