Tinna,
I don't think you have a collinearity problem, strictly speaking. Rather,
it sounds like you have a scaling problem that could be causing you
numerical problems with your estimator.
When you say the instrumented coefficient in the second stage is "blowing
up", do you mean that the estimated size of the coefficient is very large
(several+ orders of magnitude) compared to the other coefficients? Then
you could indeed have a scaling problem.
The way to find out (and to deal with the problem, if it exists) is to
rescale your endogenous variable. Just create a new variable that is 1000
or whatever times your original variable, and use it in the regression
instead. Your excluded instruments and other variables might need
rescaling too. It's easy enough to work out what to do once you see what
is going on.
Hope this helps.
Cheers,
Mark
> Dear Statalisters,
>
> I am running 2SLS estimations. The instrument used in the first stage
> is quite good according to traditional standards and tests and its
> coefficient in the first stage regression is highly significant.
> HOWEVER, the coefficient although significant is very small. I think
> this is causing collinearity (if it can be called that in this context
> - makes sense to me). The instrumented coefficient in the second stage
> is blowing up big time. However, it is significant and my
> Durbin-Wu-Hausman test is indicating endogeneity, so that the 2SLS
> would really be what is called for.
>
> 1. Someone told me that I could still trust the sign on the
> instrumented coefficient, although it is blown up. This "someone"
> says they read it "somewhere" but are not sure where. I have reached
> the end of the Internet without finding much. Can I trust the sign of
> the instrumented coefficient?
>
> 2. Can I trust my Durbin-Wu-Hausman test?
>
> 3. Any suggestion for what I should do?
>
> Tinna
>
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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: [email protected]
web: http://www.sml.hw.ac.uk/ecomes
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