Vladimir said
Dear Mr. Sabherwal,
In your first message it was said that you were going to use RE model.
Is the only justification of this specification your will to estimate
time-invariant variables? Does not the assumption of zero correlation
among effects and regressors seem too strong for your firms research?
Best,
Vladimir.
On 2/24/07, Rajiv Sabherwal <[email protected]> wrote:
> Hello,
>
> I had earlier sent the message below to statalist. However, a few
> minutes ago, it struck me that the equations I have may not be a
> "simultaneous equation model" at all. This is based partly on Kit
> Baum's message on http://www.stata.com/statalist/archive/2004-03/
> msg01120.html.
>
> In our model (given below), none of the endogeneous variables affect
> each other at that time. All the variables on the right-hand sides of
> all equations are either exogneous of lagged-endogeneous (i.e., pre-
> determined).
>
> Therefore, it would seem that simple panel regressions, rather than
> simultaneous models, would be appropriate. Am I missing something?
>
> Thanks, and best wishes,
>
> Rajiv
>
> On Feb 23, 2007, at 1:25 PM, Rajiv Sabherwal wrote:
>
> > Hello,
> >
> > A PhD student and I are trying to test a model containing
> > simultaneous equations such as the following:
> >
> > y1(t) = a1 + b11*y1(t-1) + b12*y2(t-1) +b13*y3(t-1) + b14*y4(t-1) +
> > b15*y5(t-1) + b16*x1 + b17*x2
> > y2(t) = a2 + b21*y2(t-1) + b23*y3(t-1) + b24*y4(t-1) + b25*y5(t-1)
> > + b26*x1 + b27*x2
> > y3(t) = a3 + b31*x3 + b32*x4 +b33*x5
> > y4(t) = a4 + b41*x6 + b42*x7
> > y5(t) = a5 + b51*x8 + b52*x9
But in this model the random effects estimator can NEVER be
consistent due to the presence of lagged dependent variables. There
is always the concern that exogenous regressors may not be
independent of the errors, but in the presence of LDVs that
independence of distributions is impossible.
Kit Baum, Boston College Economics
http://ideas.repec.org/e/pba1.html
An Introduction to Modern Econometrics Using Stata:
http://www.stata-press.com/books/imeus.html
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