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Re: st: constraints insufficient for unique estimate


From   Richard Williams <Richard.A.Williams.5@ND.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: constraints insufficient for unique estimate
Date   Wed, 10 Aug 2005 19:55:57 -0500

At 06:21 PM 8/10/2005 -0500, Zeynal Karaca wrote:
When I run the regression it gives me the following error:

constraints insufficient for unique estimate
redundant or inconsistent constraints

But, when I decrease the number of dummy variables for each category
to 5, the regression is going through. But I need to use all the
dummy
variables becasue all of them seperated and unique and it is crucial
for my dissertation. So, please help me out if I am missing something
in the code or should I use a different definition for the
constraint?
Does it run without the constraint? I suspect not, but try to isolate the problem.

This is an awful lot of dummies - you are sure you have excluded at least one dummy for every categorical variable? And that you are not spreading these way too thin, etc.? You may have to break down and combine some similar categories.

Personally, I suspect a perfect multicollinearity problem. In an OLS regression vars would get dropped, but maybe cnsreg instead produces the error message you saw.

You could instead do this to impose your constraint:

gen x1x2 = x1 + x2

reg Y x1x2 x3... etc.

That way, if there is perfect multicollinearity, the reg routine will respond by dropping vars rather than giving you cryptic error messages.

You might also consider whether something like -areg- can meet your needs.

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