Re: st: constrained least squares, multiple equations

[Richard Williams <Richard.A.Williams.5@nd.edu>]

At 07:49 PM 3/4/2004 -0600, Scott Merryman wrote:
> I don't believe this is the way to go -- in order to perform cross-equation
> tests you would need correlated errors.
>
> From the help on -reg3, ols-
>
> "Note that the covariance of the coefficients between equations is not 
> estimated
> under
> this option and that cross-equation tests should not be performed after
> estimation with
> ols.  For cross-equation testing, use sureg or 3sls (the default)."
I saw that too.  But, since Olena wants to use least squares, the 
implication seems to be that the covariance between equations should be 
zero.  But like I said originally, maybe 3sls would be more 
appropriate.  We probably need to know more about the substance of the 
problem here.


> Another possible way is pool the data, estimate a single fully interacted 
> model
> and test whether or not the coefficient of the interaction term is equal to
> zero. However, this does impose the assumption of homoskedasticity across the
> model.
If Y1 and Y2 and X1 and X2 stand for the values of Y and X in 2 different 
populations, then it is fairly straightforward to do this.  But, if Y1, Y2, 
X1 and X2 are 4 different variables in the same population, it gets 
trickier.  I think you'd have to duplicate the data and do various 
manipulations of the variables.  Before going to the trouble of figuring 
all that out, it would be good to have a better understanding of the 
problem first.

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