st: Re: ivreg2

[Kit Baum <baum@bc.edu>]

1) That sounds sensible.
2) As I understand it the distribution of the S-Y critical values  
differ depending on, among other things, the underlying estimator. So  
I would not make much of the fact that the CVs differ between IV-GMM  
and LIML.
3) In the context of a single FSR, the notion that the ANOVA F should  
exceed 10 is a rule of thumb suggesting that the FSR is reasonably  
strong. The first example in ivreg2 help shows a model with a single  
endogenous regressor for which F = 13.79 (zero pvalue). The Anderson  
canon. corr. LR stat. is 54, with a pvalue of 0, ad the Cragg-Donald  
min eigenvalue stat is 56, with a pvalue of zero. The null for each  
of these tests is underidentification, with rejection indicating that  
the model is identified. The latest version of ivreg2 (soon to be  
released) reformats these results to make the underlying hypotheses  
clear. However that same model has a significant Sargan test  
statistic, suggesting that the overidentifying restrictions are  
soundly rejected by the data. This implies that the instruments are  
inadequate and must be replaced. So you can have sufficiently strong  
instruments but still fail the Sargan (or Hansen J, in IV-GMM) test.  
I would worry about that in your model.

Kit

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


On Feb 4, 2007, at 2:33 AM, Sandra wrote:


>  (1) If the bias of the IV estimates cause them to approach the
> (inconsistent) OLS estimates (which are significantly positive),  
> then if
> I get larger IV estimates (compared to the OLS estimates) does that  
> mean
> my estimates would be even larger if I had strong instruments?  In  
> other
> words, would that imply my IV estimates are biased downward?
>
>  (2) I read a review by Stock and co-authors, and they mention that  
> if I
> estimate my equation using liml, then my results will be more  
> robust to
> weak instruments, further, I noticed that the Stock-Yogo critical  
> values
> are much lower, when I use LIML.  Am I making a correct  
> intepretation of
> their text?
>
>  (3) In the review by Stock and co-authors, they mention that the rule
> of thumb is that an F-test should be greater than 10.  They also  
> mention
> in the context of multiple instrumental variables the Cragg-Donald F
> statistic and the Stock-Yogo critical values.  Does this Cragg-Donald
> statistic also work in a one instrument context?  This is because,  
> when
> I look at this statistic my instruments seem to be higher than the 10%
> Stock-Yogo critical value.  If each of these statistics work as a
> sufficient condition (rather than a necessary condition) for having
> strong instruments, then I would rather report the Cragg-Donald
> statistic, considering this is statistically sound.
>
> My problem is that it is very tough to get exogenous instruments  
> for my
> variable, and this is the only instrument I have managed to come up
> with, so I would like to stick to it, if at all possible.
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